/*
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% %
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% %
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% %
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% RRRR EEEEE SSSSS IIIII ZZZZZ EEEEE %
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% R R E SS I ZZ E %
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% RRRR EEE SSS I ZZZ EEE %
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% R R E SS I ZZ E %
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% R R EEEEE SSSSS IIIII ZZZZZ EEEEE %
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% %
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% %
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% MagickCore Image Resize Methods %
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% %
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% Software Design %
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% Cristy %
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% July 1992 %
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% %
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% %
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% Copyright 1999-2019 ImageMagick Studio LLC, a non-profit organization %
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% dedicated to making software imaging solutions freely available. %
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% %
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% You may not use this file except in compliance with the License. You may %
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% obtain a copy of the License at %
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% %
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% https://imagemagick.org/script/license.php %
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% %
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% Unless required by applicable law or agreed to in writing, software %
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% distributed under the License is distributed on an "AS IS" BASIS, %
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% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
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% See the License for the specific language governing permissions and %
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% limitations under the License. %
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% %
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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%
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*/
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/*
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Include declarations.
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*/
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#include "MagickCore/studio.h"
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#include "MagickCore/accelerate-private.h"
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#include "MagickCore/artifact.h"
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#include "MagickCore/blob.h"
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#include "MagickCore/cache.h"
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#include "MagickCore/cache-view.h"
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#include "MagickCore/channel.h"
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#include "MagickCore/color.h"
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#include "MagickCore/color-private.h"
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#include "MagickCore/draw.h"
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#include "MagickCore/exception.h"
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#include "MagickCore/exception-private.h"
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#include "MagickCore/gem.h"
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#include "MagickCore/image.h"
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#include "MagickCore/image-private.h"
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#include "MagickCore/list.h"
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#include "MagickCore/memory_.h"
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#include "MagickCore/memory-private.h"
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#include "MagickCore/magick.h"
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#include "MagickCore/pixel-accessor.h"
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#include "MagickCore/property.h"
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#include "MagickCore/monitor.h"
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#include "MagickCore/monitor-private.h"
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#include "MagickCore/nt-base-private.h"
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#include "MagickCore/option.h"
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#include "MagickCore/pixel.h"
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#include "MagickCore/pixel-private.h"
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#include "MagickCore/quantum-private.h"
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#include "MagickCore/resample.h"
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#include "MagickCore/resample-private.h"
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#include "MagickCore/resize.h"
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#include "MagickCore/resize-private.h"
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#include "MagickCore/resource_.h"
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#include "MagickCore/string_.h"
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#include "MagickCore/string-private.h"
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#include "MagickCore/thread-private.h"
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#include "MagickCore/token.h"
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#include "MagickCore/utility.h"
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#include "MagickCore/utility-private.h"
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#include "MagickCore/version.h"
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#if defined(MAGICKCORE_LQR_DELEGATE)
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#include <lqr.h>
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#endif
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/*
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Typedef declarations.
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*/
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struct _ResizeFilter
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{
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double
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(*filter)(const double,const ResizeFilter *),
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(*window)(const double,const ResizeFilter *),
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support, /* filter region of support - the filter support limit */
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window_support, /* window support, usally equal to support (expert only) */
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scale, /* dimension scaling to fit window support (usally 1.0) */
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blur, /* x-scale (blur-sharpen) */
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coefficient[7]; /* cubic coefficents for BC-cubic filters */
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ResizeWeightingFunctionType
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filterWeightingType,
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windowWeightingType;
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size_t
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signature;
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};
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/*
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Forward declaractions.
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*/
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static double
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I0(double x),
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BesselOrderOne(double),
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Sinc(const double, const ResizeFilter *),
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SincFast(const double, const ResizeFilter *);
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/*
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% %
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% %
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% %
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+ F i l t e r F u n c t i o n s %
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% %
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% %
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% %
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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% These are the various filter and windowing functions that are provided.
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%
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% They are internal to this module only. See AcquireResizeFilterInfo() for
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% details of the access to these functions, via the GetResizeFilterSupport()
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% and GetResizeFilterWeight() API interface.
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%
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% The individual filter functions have this format...
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%
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% static MagickRealtype *FilterName(const double x,const double support)
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%
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% A description of each parameter follows:
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%
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% o x: the distance from the sampling point generally in the range of 0 to
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% support. The GetResizeFilterWeight() ensures this a positive value.
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%
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% o resize_filter: current filter information. This allows function to
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% access support, and possibly other pre-calculated information defining
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% the functions.
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%
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*/
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static double Blackman(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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/*
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Blackman: 2nd order cosine windowing function:
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0.42 + 0.5 cos(pi x) + 0.08 cos(2pi x)
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Refactored by Chantal Racette and Nicolas Robidoux to one trig call and
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five flops.
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*/
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const double cosine=cos((double) (MagickPI*x));
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magick_unreferenced(resize_filter);
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return(0.34+cosine*(0.5+cosine*0.16));
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}
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static double Bohman(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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/*
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Bohman: 2rd Order cosine windowing function:
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(1-x) cos(pi x) + sin(pi x) / pi.
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Refactored by Nicolas Robidoux to one trig call, one sqrt call, and 7 flops,
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taking advantage of the fact that the support of Bohman is 1.0 (so that we
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know that sin(pi x) >= 0).
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*/
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const double cosine=cos((double) (MagickPI*x));
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const double sine=sqrt(1.0-cosine*cosine);
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magick_unreferenced(resize_filter);
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return((1.0-x)*cosine+(1.0/MagickPI)*sine);
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}
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static double Box(const double magick_unused(x),
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const ResizeFilter *magick_unused(resize_filter))
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{
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magick_unreferenced(x);
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magick_unreferenced(resize_filter);
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/*
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A Box filter is a equal weighting function (all weights equal).
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DO NOT LIMIT results by support or resize point sampling will work
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as it requests points beyond its normal 0.0 support size.
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*/
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return(1.0);
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}
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static double Cosine(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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magick_unreferenced(resize_filter);
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/*
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Cosine window function:
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cos((pi/2)*x).
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*/
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return((double)cos((double) (MagickPI2*x)));
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}
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static double CubicBC(const double x,const ResizeFilter *resize_filter)
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{
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/*
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Cubic Filters using B,C determined values:
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Mitchell-Netravali B = 1/3 C = 1/3 "Balanced" cubic spline filter
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Catmull-Rom B = 0 C = 1/2 Interpolatory and exact on linears
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Spline B = 1 C = 0 B-Spline Gaussian approximation
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Hermite B = 0 C = 0 B-Spline interpolator
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See paper by Mitchell and Netravali, Reconstruction Filters in Computer
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Graphics Computer Graphics, Volume 22, Number 4, August 1988
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http://www.cs.utexas.edu/users/fussell/courses/cs384g/lectures/mitchell/
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Mitchell.pdf.
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Coefficents are determined from B,C values:
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P0 = ( 6 - 2*B )/6 = coeff[0]
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P1 = 0
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P2 = (-18 +12*B + 6*C )/6 = coeff[1]
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P3 = ( 12 - 9*B - 6*C )/6 = coeff[2]
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Q0 = ( 8*B +24*C )/6 = coeff[3]
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Q1 = ( -12*B -48*C )/6 = coeff[4]
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Q2 = ( 6*B +30*C )/6 = coeff[5]
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Q3 = ( - 1*B - 6*C )/6 = coeff[6]
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which are used to define the filter:
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P0 + P1*x + P2*x^2 + P3*x^3 0 <= x < 1
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Q0 + Q1*x + Q2*x^2 + Q3*x^3 1 <= x < 2
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which ensures function is continuous in value and derivative (slope).
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*/
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if (x < 1.0)
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return(resize_filter->coefficient[0]+x*(x*
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(resize_filter->coefficient[1]+x*resize_filter->coefficient[2])));
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if (x < 2.0)
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return(resize_filter->coefficient[3]+x*(resize_filter->coefficient[4]+x*
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(resize_filter->coefficient[5]+x*resize_filter->coefficient[6])));
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return(0.0);
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}
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static double CubicSpline(const double x,const ResizeFilter *resize_filter)
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{
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if (resize_filter->support <= 2.0)
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{
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/*
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2-lobe Spline filter.
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*/
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if (x < 1.0)
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return(((x-9.0/5.0)*x-1.0/5.0)*x+1.0);
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if (x < 2.0)
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return(((-1.0/3.0*(x-1.0)+4.0/5.0)*(x-1.0)-7.0/15.0)*(x-1.0));
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return(0.0);
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}
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if (resize_filter->support <= 3.0)
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{
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/*
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3-lobe Spline filter.
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*/
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if (x < 1.0)
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return(((13.0/11.0*x-453.0/209.0)*x-3.0/209.0)*x+1.0);
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if (x < 2.0)
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return(((-6.0/11.0*(x-1.0)+270.0/209.0)*(x-1.0)-156.0/209.0)*(x-1.0));
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if (x < 3.0)
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return(((1.0/11.0*(x-2.0)-45.0/209.0)*(x-2.0)+26.0/209.0)*(x-2.0));
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return(0.0);
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}
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/*
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4-lobe Spline filter.
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*/
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if (x < 1.0)
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return(((49.0/41.0*x-6387.0/2911.0)*x-3.0/2911.0)*x+1.0);
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if (x < 2.0)
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return(((-24.0/41.0*(x-1.0)+4032.0/2911.0)*(x-1.0)-2328.0/2911.0)*(x-1.0));
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if (x < 3.0)
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return(((6.0/41.0*(x-2.0)-1008.0/2911.0)*(x-2.0)+582.0/2911.0)*(x-2.0));
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if (x < 4.0)
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return(((-1.0/41.0*(x-3.0)+168.0/2911.0)*(x-3.0)-97.0/2911.0)*(x-3.0));
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return(0.0);
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}
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static double Gaussian(const double x,const ResizeFilter *resize_filter)
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{
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/*
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Gaussian with a sigma = 1/2 (or as user specified)
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Gaussian Formula (1D) ...
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exp( -(x^2)/((2.0*sigma^2) ) / (sqrt(2*PI)*sigma^2))
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Gaussian Formula (2D) ...
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exp( -(x^2+y^2)/(2.0*sigma^2) ) / (PI*sigma^2) )
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or for radius
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exp( -(r^2)/(2.0*sigma^2) ) / (PI*sigma^2) )
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Note that it is only a change from 1-d to radial form is in the
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normalization multiplier which is not needed or used when Gaussian is used
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as a filter.
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The constants are pre-calculated...
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coeff[0]=sigma;
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coeff[1]=1.0/(2.0*sigma^2);
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coeff[2]=1.0/(sqrt(2*PI)*sigma^2);
|
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exp( -coeff[1]*(x^2)) ) * coeff[2];
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However the multiplier coeff[1] is need, the others are informative only.
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This separates the gaussian 'sigma' value from the 'blur/support'
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settings allowing for its use in special 'small sigma' gaussians,
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without the filter 'missing' pixels because the support becomes too
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small.
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*/
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return(exp((double)(-resize_filter->coefficient[1]*x*x)));
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}
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static double Hann(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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/*
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Cosine window function:
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0.5+0.5*cos(pi*x).
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*/
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const double cosine=cos((double) (MagickPI*x));
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magick_unreferenced(resize_filter);
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return(0.5+0.5*cosine);
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}
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static double Hamming(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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/*
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Offset cosine window function:
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.54 + .46 cos(pi x).
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*/
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const double cosine=cos((double) (MagickPI*x));
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magick_unreferenced(resize_filter);
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return(0.54+0.46*cosine);
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}
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static double Jinc(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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magick_unreferenced(resize_filter);
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/*
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See Pratt "Digital Image Processing" p.97 for Jinc/Bessel functions.
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http://mathworld.wolfram.com/JincFunction.html and page 11 of
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http://www.ph.ed.ac.uk/%7ewjh/teaching/mo/slides/lens/lens.pdf
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|
The original "zoom" program by Paul Heckbert called this "Bessel". But
|
really it is more accurately named "Jinc".
|
*/
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if (x == 0.0)
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return(0.5*MagickPI);
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return(BesselOrderOne(MagickPI*x)/x);
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}
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static double Kaiser(const double x,const ResizeFilter *resize_filter)
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{
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/*
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Kaiser Windowing Function (bessel windowing)
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I0( beta * sqrt( 1-x^2) ) / IO(0)
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Beta (coeff[0]) is a free value from 5 to 8 (defaults to 6.5).
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However it is typically defined in terms of Alpha*PI
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The normalization factor (coeff[1]) is not actually needed,
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but without it the filters has a large value at x=0 making it
|
difficult to compare the function with other windowing functions.
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*/
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return(resize_filter->coefficient[1]*I0(resize_filter->coefficient[0]*
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sqrt((double) (1.0-x*x))));
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}
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static double Lagrange(const double x,const ResizeFilter *resize_filter)
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{
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double
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value;
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register ssize_t
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i;
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ssize_t
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n,
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order;
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/*
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Lagrange piecewise polynomial fit of sinc: N is the 'order' of the lagrange
|
function and depends on the overall support window size of the filter. That
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is: for a support of 2, it gives a lagrange-4 (piecewise cubic function).
|
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"n" identifies the piece of the piecewise polynomial.
|
|
See Survey: Interpolation Methods, IEEE Transactions on Medical Imaging,
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Vol 18, No 11, November 1999, p1049-1075, -- Equation 27 on p1064.
|
*/
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if (x > resize_filter->support)
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return(0.0);
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order=(ssize_t) (2.0*resize_filter->window_support); /* number of pieces */
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n=(ssize_t) (resize_filter->window_support+x);
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value=1.0f;
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for (i=0; i < order; i++)
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if (i != n)
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value*=(n-i-x)/(n-i);
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return(value);
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}
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static double Quadratic(const double x,
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const ResizeFilter *magick_unused(resize_filter))
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{
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magick_unreferenced(resize_filter);
|
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/*
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2rd order (quadratic) B-Spline approximation of Gaussian.
|
*/
|
if (x < 0.5)
|
return(0.75-x*x);
|
if (x < 1.5)
|
return(0.5*(x-1.5)*(x-1.5));
|
return(0.0);
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}
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static double Sinc(const double x,
|
const ResizeFilter *magick_unused(resize_filter))
|
{
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magick_unreferenced(resize_filter);
|
|
/*
|
Scaled sinc(x) function using a trig call:
|
sinc(x) == sin(pi x)/(pi x).
|
*/
|
if (x != 0.0)
|
{
|
const double alpha=(double) (MagickPI*x);
|
return(sin((double) alpha)/alpha);
|
}
|
return((double) 1.0);
|
}
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|
static double SincFast(const double x,
|
const ResizeFilter *magick_unused(resize_filter))
|
{
|
magick_unreferenced(resize_filter);
|
|
/*
|
Approximations of the sinc function sin(pi x)/(pi x) over the interval
|
[-4,4] constructed by Nicolas Robidoux and Chantal Racette with funding
|
from the Natural Sciences and Engineering Research Council of Canada.
|
|
Although the approximations are polynomials (for low order of
|
approximation) and quotients of polynomials (for higher order of
|
approximation) and consequently are similar in form to Taylor polynomials /
|
Pade approximants, the approximations are computed with a completely
|
different technique.
|
|
Summary: These approximations are "the best" in terms of bang (accuracy)
|
for the buck (flops). More specifically: Among the polynomial quotients
|
that can be computed using a fixed number of flops (with a given "+ - * /
|
budget"), the chosen polynomial quotient is the one closest to the
|
approximated function with respect to maximum absolute relative error over
|
the given interval.
|
|
The Remez algorithm, as implemented in the boost library's minimax package,
|
is the key to the construction: http://www.boost.org/doc/libs/1_36_0/libs/
|
math/doc/sf_and_dist/html/math_toolkit/backgrounders/remez.html
|
|
If outside of the interval of approximation, use the standard trig formula.
|
*/
|
if (x > 4.0)
|
{
|
const double alpha=(double) (MagickPI*x);
|
return(sin((double) alpha)/alpha);
|
}
|
{
|
/*
|
The approximations only depend on x^2 (sinc is an even function).
|
*/
|
const double xx = x*x;
|
#if MAGICKCORE_QUANTUM_DEPTH <= 8
|
/*
|
Maximum absolute relative error 6.3e-6 < 1/2^17.
|
*/
|
const double c0 = 0.173610016489197553621906385078711564924e-2L;
|
const double c1 = -0.384186115075660162081071290162149315834e-3L;
|
const double c2 = 0.393684603287860108352720146121813443561e-4L;
|
const double c3 = -0.248947210682259168029030370205389323899e-5L;
|
const double c4 = 0.107791837839662283066379987646635416692e-6L;
|
const double c5 = -0.324874073895735800961260474028013982211e-8L;
|
const double c6 = 0.628155216606695311524920882748052490116e-10L;
|
const double c7 = -0.586110644039348333520104379959307242711e-12L;
|
const double p =
|
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*c7))))));
|
return((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)*p);
|
#elif MAGICKCORE_QUANTUM_DEPTH <= 16
|
/*
|
Max. abs. rel. error 2.2e-8 < 1/2^25.
|
*/
|
const double c0 = 0.173611107357320220183368594093166520811e-2L;
|
const double c1 = -0.384240921114946632192116762889211361285e-3L;
|
const double c2 = 0.394201182359318128221229891724947048771e-4L;
|
const double c3 = -0.250963301609117217660068889165550534856e-5L;
|
const double c4 = 0.111902032818095784414237782071368805120e-6L;
|
const double c5 = -0.372895101408779549368465614321137048875e-8L;
|
const double c6 = 0.957694196677572570319816780188718518330e-10L;
|
const double c7 = -0.187208577776590710853865174371617338991e-11L;
|
const double c8 = 0.253524321426864752676094495396308636823e-13L;
|
const double c9 = -0.177084805010701112639035485248501049364e-15L;
|
const double p =
|
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*(c7+xx*(c8+xx*c9))))))));
|
return((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)*p);
|
#else
|
/*
|
Max. abs. rel. error 1.2e-12 < 1/2^39.
|
*/
|
const double c0 = 0.173611111110910715186413700076827593074e-2L;
|
const double c1 = -0.289105544717893415815859968653611245425e-3L;
|
const double c2 = 0.206952161241815727624413291940849294025e-4L;
|
const double c3 = -0.834446180169727178193268528095341741698e-6L;
|
const double c4 = 0.207010104171026718629622453275917944941e-7L;
|
const double c5 = -0.319724784938507108101517564300855542655e-9L;
|
const double c6 = 0.288101675249103266147006509214934493930e-11L;
|
const double c7 = -0.118218971804934245819960233886876537953e-13L;
|
const double p =
|
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*c7))))));
|
const double d0 = 1.0L;
|
const double d1 = 0.547981619622284827495856984100563583948e-1L;
|
const double d2 = 0.134226268835357312626304688047086921806e-2L;
|
const double d3 = 0.178994697503371051002463656833597608689e-4L;
|
const double d4 = 0.114633394140438168641246022557689759090e-6L;
|
const double q = d0+xx*(d1+xx*(d2+xx*(d3+xx*d4)));
|
return((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)/q*p);
|
#endif
|
}
|
}
|
|
static double Triangle(const double x,
|
const ResizeFilter *magick_unused(resize_filter))
|
{
|
magick_unreferenced(resize_filter);
|
|
/*
|
1st order (linear) B-Spline, bilinear interpolation, Tent 1D filter, or
|
a Bartlett 2D Cone filter. Also used as a Bartlett Windowing function
|
for Sinc().
|
*/
|
if (x < 1.0)
|
return(1.0-x);
|
return(0.0);
|
}
|
|
static double Welch(const double x,
|
const ResizeFilter *magick_unused(resize_filter))
|
{
|
magick_unreferenced(resize_filter);
|
|
/*
|
Welch parabolic windowing filter.
|
*/
|
if (x < 1.0)
|
return(1.0-x*x);
|
return(0.0);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
+ A c q u i r e R e s i z e F i l t e r %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% AcquireResizeFilter() allocates the ResizeFilter structure. Choose from
|
% these filters:
|
%
|
% FIR (Finite impulse Response) Filters
|
% Box Triangle Quadratic
|
% Spline Hermite Catrom
|
% Mitchell
|
%
|
% IIR (Infinite impulse Response) Filters
|
% Gaussian Sinc Jinc (Bessel)
|
%
|
% Windowed Sinc/Jinc Filters
|
% Blackman Bohman Lanczos
|
% Hann Hamming Cosine
|
% Kaiser Welch Parzen
|
% Bartlett
|
%
|
% Special Purpose Filters
|
% Cubic SincFast LanczosSharp Lanczos2 Lanczos2Sharp
|
% Robidoux RobidouxSharp
|
%
|
% The users "-filter" selection is used to lookup the default 'expert'
|
% settings for that filter from a internal table. However any provided
|
% 'expert' settings (see below) may override this selection.
|
%
|
% FIR filters are used as is, and are limited to that filters support window
|
% (unless over-ridden). 'Gaussian' while classed as an IIR filter, is also
|
% simply clipped by its support size (currently 1.5 or approximately 3*sigma
|
% as recommended by many references)
|
%
|
% The special a 'cylindrical' filter flag will promote the default 4-lobed
|
% Windowed Sinc filter to a 3-lobed Windowed Jinc equivalent, which is better
|
% suited to this style of image resampling. This typically happens when using
|
% such a filter for images distortions.
|
%
|
% SPECIFIC FILTERS:
|
%
|
% Directly requesting 'Sinc', 'Jinc' function as a filter will force the use
|
% of function without any windowing, or promotion for cylindrical usage. This
|
% is not recommended, except by image processing experts, especially as part
|
% of expert option filter function selection.
|
%
|
% Two forms of the 'Sinc' function are available: Sinc and SincFast. Sinc is
|
% computed using the traditional sin(pi*x)/(pi*x); it is selected if the user
|
% specifically specifies the use of a Sinc filter. SincFast uses highly
|
% accurate (and fast) polynomial (low Q) and rational (high Q) approximations,
|
% and will be used by default in most cases.
|
%
|
% The Lanczos filter is a special 3-lobed Sinc-windowed Sinc filter (promoted
|
% to Jinc-windowed Jinc for cylindrical (Elliptical Weighted Average) use).
|
% The Sinc version is the most popular windowed filter.
|
%
|
% LanczosSharp is a slightly sharpened (blur=0.9812505644269356 < 1) form of
|
% the Lanczos filter, specifically designed for EWA distortion (as a
|
% Jinc-Jinc); it can also be used as a slightly sharper orthogonal Lanczos
|
% (Sinc-Sinc) filter. The chosen blur value comes as close as possible to
|
% satisfying the following condition without changing the character of the
|
% corresponding EWA filter:
|
%
|
% 'No-Op' Vertical and Horizontal Line Preservation Condition: Images with
|
% only vertical or horizontal features are preserved when performing 'no-op"
|
% with EWA distortion.
|
%
|
% The Lanczos2 and Lanczos2Sharp filters are 2-lobe versions of the Lanczos
|
% filters. The 'sharp' version uses a blur factor of 0.9549963639785485,
|
% again chosen because the resulting EWA filter comes as close as possible to
|
% satisfying the above condition.
|
%
|
% Robidoux is another filter tuned for EWA. It is the Keys cubic filter
|
% defined by B=(228 - 108 sqrt(2))/199. Robidoux satisfies the "'No-Op'
|
% Vertical and Horizontal Line Preservation Condition" exactly, and it
|
% moderately blurs high frequency 'pixel-hash' patterns under no-op. It turns
|
% out to be close to both Mitchell and Lanczos2Sharp. For example, its first
|
% crossing is at (36 sqrt(2) + 123)/(72 sqrt(2) + 47), almost the same as the
|
% first crossing of Mitchell and Lanczos2Sharp.
|
%
|
% RodidouxSharp is a slightly sharper version of Rodidoux, some believe it
|
% is too sharp. It is designed to minimize the maximum possible change in
|
% a pixel value which is at one of the extremes (e.g., 0 or 255) under no-op
|
% conditions. Amazingly Mitchell falls roughly between Rodidoux and
|
% RodidouxSharp, though this seems to have been pure coincidence.
|
%
|
% 'EXPERT' OPTIONS:
|
%
|
% These artifact "defines" are not recommended for production use without
|
% expert knowledge of resampling, filtering, and the effects they have on the
|
% resulting resampled (resized or distorted) image.
|
%
|
% They can be used to override any and all filter default, and it is
|
% recommended you make good use of "filter:verbose" to make sure that the
|
% overall effect of your selection (before and after) is as expected.
|
%
|
% "filter:verbose" controls whether to output the exact results of the
|
% filter selections made, as well as plotting data for graphing the
|
% resulting filter over the filters support range.
|
%
|
% "filter:filter" select the main function associated with this filter
|
% name, as the weighting function of the filter. This can be used to
|
% set a windowing function as a weighting function, for special
|
% purposes, such as graphing.
|
%
|
% If a "filter:window" operation has not been provided, a 'Box'
|
% windowing function will be set to denote that no windowing function is
|
% being used.
|
%
|
% "filter:window" Select this windowing function for the filter. While any
|
% filter could be used as a windowing function, using the 'first lobe' of
|
% that filter over the whole support window, using a non-windowing
|
% function is not advisible. If no weighting filter function is specified
|
% a 'SincFast' filter is used.
|
%
|
% "filter:lobes" Number of lobes to use for the Sinc/Jinc filter. This a
|
% simpler method of setting filter support size that will correctly
|
% handle the Sinc/Jinc switch for an operators filtering requirements.
|
% Only integers should be given.
|
%
|
% "filter:support" Set the support size for filtering to the size given.
|
% This not recommended for Sinc/Jinc windowed filters (lobes should be
|
% used instead). This will override any 'filter:lobes' option.
|
%
|
% "filter:win-support" Scale windowing function to this size instead. This
|
% causes the windowing (or self-windowing Lagrange filter) to act is if
|
% the support window it much much larger than what is actually supplied
|
% to the calling operator. The filter however is still clipped to the
|
% real support size given, by the support range supplied to the caller.
|
% If unset this will equal the normal filter support size.
|
%
|
% "filter:blur" Scale the filter and support window by this amount. A value
|
% of > 1 will generally result in a more blurred image with more ringing
|
% effects, while a value <1 will sharpen the resulting image with more
|
% aliasing effects.
|
%
|
% "filter:sigma" The sigma value to use for the Gaussian filter only.
|
% Defaults to '1/2'. Using a different sigma effectively provides a
|
% method of using the filter as a 'blur' convolution. Particularly when
|
% using it for Distort.
|
%
|
% "filter:b"
|
% "filter:c" Override the preset B,C values for a Cubic filter.
|
% If only one of these are given it is assumes to be a 'Keys' type of
|
% filter such that B+2C=1, where Keys 'alpha' value = C.
|
%
|
% Examples:
|
%
|
% Set a true un-windowed Sinc filter with 10 lobes (very slow):
|
% -define filter:filter=Sinc
|
% -define filter:lobes=8
|
%
|
% Set an 8 lobe Lanczos (Sinc or Jinc) filter:
|
% -filter Lanczos
|
% -define filter:lobes=8
|
%
|
% The format of the AcquireResizeFilter method is:
|
%
|
% ResizeFilter *AcquireResizeFilter(const Image *image,
|
% const FilterType filter_type,const MagickBooleanType cylindrical,
|
% ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o filter: the filter type, defining a preset filter, window and support.
|
% The artifact settings listed above will override those selections.
|
%
|
% o blur: blur the filter by this amount, use 1.0 if unknown. Image
|
% artifact "filter:blur" will override this API call usage, including any
|
% internal change (such as for cylindrical usage).
|
%
|
% o radial: use a 1D orthogonal filter (Sinc) or 2D cylindrical (radial)
|
% filter (Jinc).
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickPrivate ResizeFilter *AcquireResizeFilter(const Image *image,
|
const FilterType filter,const MagickBooleanType cylindrical,
|
ExceptionInfo *exception)
|
{
|
const char
|
*artifact;
|
|
FilterType
|
filter_type,
|
window_type;
|
|
double
|
B,
|
C,
|
value;
|
|
register ResizeFilter
|
*resize_filter;
|
|
/*
|
Table Mapping given Filter, into Weighting and Windowing functions.
|
A 'Box' windowing function means its a simble non-windowed filter.
|
An 'SincFast' filter function could be upgraded to a 'Jinc' filter if a
|
"cylindrical" is requested, unless a 'Sinc' or 'SincFast' filter was
|
specifically requested by the user.
|
|
WARNING: The order of this table must match the order of the FilterType
|
enumeration specified in "resample.h", or the filter names will not match
|
the filter being setup.
|
|
You can check filter setups with the "filter:verbose" expert setting.
|
*/
|
static struct
|
{
|
FilterType
|
filter,
|
window;
|
} const mapping[SentinelFilter] =
|
{
|
{ UndefinedFilter, BoxFilter }, /* Undefined (default to Box) */
|
{ PointFilter, BoxFilter }, /* SPECIAL: Nearest neighbour */
|
{ BoxFilter, BoxFilter }, /* Box averaging filter */
|
{ TriangleFilter, BoxFilter }, /* Linear interpolation filter */
|
{ HermiteFilter, BoxFilter }, /* Hermite interpolation filter */
|
{ SincFastFilter, HannFilter }, /* Hann -- cosine-sinc */
|
{ SincFastFilter, HammingFilter }, /* Hamming -- '' variation */
|
{ SincFastFilter, BlackmanFilter }, /* Blackman -- 2*cosine-sinc */
|
{ GaussianFilter, BoxFilter }, /* Gaussian blur filter */
|
{ QuadraticFilter, BoxFilter }, /* Quadratic Gaussian approx */
|
{ CubicFilter, BoxFilter }, /* General Cubic Filter, Spline */
|
{ CatromFilter, BoxFilter }, /* Cubic-Keys interpolator */
|
{ MitchellFilter, BoxFilter }, /* 'Ideal' Cubic-Keys filter */
|
{ JincFilter, BoxFilter }, /* Raw 3-lobed Jinc function */
|
{ SincFilter, BoxFilter }, /* Raw 4-lobed Sinc function */
|
{ SincFastFilter, BoxFilter }, /* Raw fast sinc ("Pade"-type) */
|
{ SincFastFilter, KaiserFilter }, /* Kaiser -- square root-sinc */
|
{ LanczosFilter, WelchFilter }, /* Welch -- parabolic (3 lobe) */
|
{ SincFastFilter, CubicFilter }, /* Parzen -- cubic-sinc */
|
{ SincFastFilter, BohmanFilter }, /* Bohman -- 2*cosine-sinc */
|
{ SincFastFilter, TriangleFilter }, /* Bartlett -- triangle-sinc */
|
{ LagrangeFilter, BoxFilter }, /* Lagrange self-windowing */
|
{ LanczosFilter, LanczosFilter }, /* Lanczos Sinc-Sinc filters */
|
{ LanczosSharpFilter, LanczosSharpFilter }, /* | these require */
|
{ Lanczos2Filter, Lanczos2Filter }, /* | special handling */
|
{ Lanczos2SharpFilter, Lanczos2SharpFilter },
|
{ RobidouxFilter, BoxFilter }, /* Cubic Keys tuned for EWA */
|
{ RobidouxSharpFilter, BoxFilter }, /* Sharper Cubic Keys for EWA */
|
{ LanczosFilter, CosineFilter }, /* Cosine window (3 lobes) */
|
{ SplineFilter, BoxFilter }, /* Spline Cubic Filter */
|
{ LanczosRadiusFilter, LanczosFilter }, /* Lanczos with integer radius */
|
{ CubicSplineFilter, BoxFilter }, /* CubicSpline (2/3/4 lobes) */
|
};
|
/*
|
Table mapping the filter/window from the above table to an actual function.
|
The default support size for that filter as a weighting function, the range
|
to scale with to use that function as a sinc windowing function, (typ 1.0).
|
|
Note that the filter_type -> function is 1 to 1 except for Sinc(),
|
SincFast(), and CubicBC() functions, which may have multiple filter to
|
function associations.
|
|
See "filter:verbose" handling below for the function -> filter mapping.
|
*/
|
static struct
|
{
|
double
|
(*function)(const double,const ResizeFilter*),
|
support, /* Default lobes/support size of the weighting filter. */
|
scale, /* Support when function used as a windowing function
|
Typically equal to the location of the first zero crossing. */
|
B,C; /* BC-spline coefficients, ignored if not a CubicBC filter. */
|
ResizeWeightingFunctionType weightingFunctionType;
|
} const filters[SentinelFilter] =
|
{
|
/* .--- support window (if used as a Weighting Function)
|
| .--- first crossing (if used as a Windowing Function)
|
| | .--- B value for Cubic Function
|
| | | .---- C value for Cubic Function
|
| | | | */
|
{ Box, 0.5, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Undefined (default to Box) */
|
{ Box, 0.0, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Point (special handling) */
|
{ Box, 0.5, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Box */
|
{ Triangle, 1.0, 1.0, 0.0, 0.0, TriangleWeightingFunction }, /* Triangle */
|
{ CubicBC, 1.0, 1.0, 0.0, 0.0, CubicBCWeightingFunction }, /* Hermite (cubic B=C=0) */
|
{ Hann, 1.0, 1.0, 0.0, 0.0, HannWeightingFunction }, /* Hann, cosine window */
|
{ Hamming, 1.0, 1.0, 0.0, 0.0, HammingWeightingFunction }, /* Hamming, '' variation */
|
{ Blackman, 1.0, 1.0, 0.0, 0.0, BlackmanWeightingFunction }, /* Blackman, 2*cosine window */
|
{ Gaussian, 2.0, 1.5, 0.0, 0.0, GaussianWeightingFunction }, /* Gaussian */
|
{ Quadratic, 1.5, 1.5, 0.0, 0.0, QuadraticWeightingFunction },/* Quadratic gaussian */
|
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* General Cubic Filter */
|
{ CubicBC, 2.0, 1.0, 0.0, 0.5, CubicBCWeightingFunction }, /* Catmull-Rom (B=0,C=1/2) */
|
{ CubicBC, 2.0, 8.0/7.0, 1./3., 1./3., CubicBCWeightingFunction }, /* Mitchell (B=C=1/3) */
|
{ Jinc, 3.0, 1.2196698912665045, 0.0, 0.0, JincWeightingFunction }, /* Raw 3-lobed Jinc */
|
{ Sinc, 4.0, 1.0, 0.0, 0.0, SincWeightingFunction }, /* Raw 4-lobed Sinc */
|
{ SincFast, 4.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Raw fast sinc ("Pade"-type) */
|
{ Kaiser, 1.0, 1.0, 0.0, 0.0, KaiserWeightingFunction }, /* Kaiser (square root window) */
|
{ Welch, 1.0, 1.0, 0.0, 0.0, WelchWeightingFunction }, /* Welch (parabolic window) */
|
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* Parzen (B-Spline window) */
|
{ Bohman, 1.0, 1.0, 0.0, 0.0, BohmanWeightingFunction }, /* Bohman, 2*Cosine window */
|
{ Triangle, 1.0, 1.0, 0.0, 0.0, TriangleWeightingFunction }, /* Bartlett (triangle window) */
|
{ Lagrange, 2.0, 1.0, 0.0, 0.0, LagrangeWeightingFunction }, /* Lagrange sinc approximation */
|
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, 3-lobed Sinc-Sinc */
|
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, Sharpened */
|
{ SincFast, 2.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, 2-lobed */
|
{ SincFast, 2.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos2, sharpened */
|
/* Robidoux: Keys cubic close to Lanczos2D sharpened */
|
{ CubicBC, 2.0, 1.1685777620836932,
|
0.37821575509399867, 0.31089212245300067, CubicBCWeightingFunction },
|
/* RobidouxSharp: Sharper version of Robidoux */
|
{ CubicBC, 2.0, 1.105822933719019,
|
0.2620145123990142, 0.3689927438004929, CubicBCWeightingFunction },
|
{ Cosine, 1.0, 1.0, 0.0, 0.0, CosineWeightingFunction }, /* Low level cosine window */
|
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* Cubic B-Spline (B=1,C=0) */
|
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, Interger Radius */
|
{ CubicSpline,2.0, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Spline Lobes 2-lobed */
|
};
|
/*
|
The known zero crossings of the Jinc() or more accurately the Jinc(x*PI)
|
function being used as a filter. It is used by the "filter:lobes" expert
|
setting and for 'lobes' for Jinc functions in the previous table. This way
|
users do not have to deal with the highly irrational lobe sizes of the Jinc
|
filter.
|
|
Values taken from
|
http://cose.math.bas.bg/webMathematica/webComputing/BesselZeros.jsp
|
using Jv-function with v=1, then dividing by PI.
|
*/
|
static double
|
jinc_zeros[16] =
|
{
|
1.2196698912665045,
|
2.2331305943815286,
|
3.2383154841662362,
|
4.2410628637960699,
|
5.2427643768701817,
|
6.2439216898644877,
|
7.2447598687199570,
|
8.2453949139520427,
|
9.2458926849494673,
|
10.246293348754916,
|
11.246622794877883,
|
12.246898461138105,
|
13.247132522181061,
|
14.247333735806849,
|
15.247508563037300,
|
16.247661874700962
|
};
|
|
/*
|
Allocate resize filter.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(UndefinedFilter < filter && filter < SentinelFilter);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
(void) exception;
|
resize_filter=(ResizeFilter *) AcquireCriticalMemory(sizeof(*resize_filter));
|
(void) memset(resize_filter,0,sizeof(*resize_filter));
|
/*
|
Defaults for the requested filter.
|
*/
|
filter_type=mapping[filter].filter;
|
window_type=mapping[filter].window;
|
resize_filter->blur=1.0;
|
/* Promote 1D Windowed Sinc Filters to a 2D Windowed Jinc filters */
|
if ((cylindrical != MagickFalse) && (filter_type == SincFastFilter) &&
|
(filter != SincFastFilter))
|
filter_type=JincFilter; /* 1D Windowed Sinc => 2D Windowed Jinc filters */
|
|
/* Expert filter setting override */
|
artifact=GetImageArtifact(image,"filter:filter");
|
if (IsStringTrue(artifact) != MagickFalse)
|
{
|
ssize_t
|
option;
|
|
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
|
if ((UndefinedFilter < option) && (option < SentinelFilter))
|
{ /* Raw filter request - no window function. */
|
filter_type=(FilterType) option;
|
window_type=BoxFilter;
|
}
|
/* Filter override with a specific window function. */
|
artifact=GetImageArtifact(image,"filter:window");
|
if (artifact != (const char *) NULL)
|
{
|
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
|
if ((UndefinedFilter < option) && (option < SentinelFilter))
|
window_type=(FilterType) option;
|
}
|
}
|
else
|
{
|
/* Window specified, but no filter function? Assume Sinc/Jinc. */
|
artifact=GetImageArtifact(image,"filter:window");
|
if (artifact != (const char *) NULL)
|
{
|
ssize_t
|
option;
|
|
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
|
if ((UndefinedFilter < option) && (option < SentinelFilter))
|
{
|
filter_type= cylindrical != MagickFalse ? JincFilter
|
: SincFastFilter;
|
window_type=(FilterType) option;
|
}
|
}
|
}
|
|
/* Assign the real functions to use for the filters selected. */
|
resize_filter->filter=filters[filter_type].function;
|
resize_filter->support=filters[filter_type].support;
|
resize_filter->filterWeightingType=filters[filter_type].weightingFunctionType;
|
resize_filter->window=filters[window_type].function;
|
resize_filter->windowWeightingType=filters[window_type].weightingFunctionType;
|
resize_filter->scale=filters[window_type].scale;
|
resize_filter->signature=MagickCoreSignature;
|
|
/* Filter Modifications for orthogonal/cylindrical usage */
|
if (cylindrical != MagickFalse)
|
switch (filter_type)
|
{
|
case BoxFilter:
|
/* Support for Cylindrical Box should be sqrt(2)/2 */
|
resize_filter->support=(double) MagickSQ1_2;
|
break;
|
case LanczosFilter:
|
case LanczosSharpFilter:
|
case Lanczos2Filter:
|
case Lanczos2SharpFilter:
|
case LanczosRadiusFilter:
|
resize_filter->filter=filters[JincFilter].function;
|
resize_filter->window=filters[JincFilter].function;
|
resize_filter->scale=filters[JincFilter].scale;
|
/* number of lobes (support window size) remain unchanged */
|
break;
|
default:
|
break;
|
}
|
/* Global Sharpening (regardless of orthoginal/cylindrical) */
|
switch (filter_type)
|
{
|
case LanczosSharpFilter:
|
resize_filter->blur *= 0.9812505644269356;
|
break;
|
case Lanczos2SharpFilter:
|
resize_filter->blur *= 0.9549963639785485;
|
break;
|
/* case LanczosRadius: blur adjust is done after lobes */
|
default:
|
break;
|
}
|
|
/*
|
Expert Option Modifications.
|
*/
|
|
/* User Gaussian Sigma Override - no support change */
|
if ((resize_filter->filter == Gaussian) ||
|
(resize_filter->window == Gaussian) ) {
|
value=0.5; /* guassian sigma default, half pixel */
|
artifact=GetImageArtifact(image,"filter:sigma");
|
if (artifact != (const char *) NULL)
|
value=StringToDouble(artifact,(char **) NULL);
|
/* Define coefficents for Gaussian */
|
resize_filter->coefficient[0]=value; /* note sigma too */
|
resize_filter->coefficient[1]=PerceptibleReciprocal(2.0*value*value); /* sigma scaling */
|
resize_filter->coefficient[2]=PerceptibleReciprocal(Magick2PI*value*value);
|
/* normalization - not actually needed or used! */
|
if ( value > 0.5 )
|
resize_filter->support *= 2*value; /* increase support linearly */
|
}
|
|
/* User Kaiser Alpha Override - no support change */
|
if ((resize_filter->filter == Kaiser) ||
|
(resize_filter->window == Kaiser) ) {
|
value=6.5; /* default beta value for Kaiser bessel windowing function */
|
artifact=GetImageArtifact(image,"filter:alpha"); /* FUTURE: depreciate */
|
if (artifact != (const char *) NULL)
|
value=StringToDouble(artifact,(char **) NULL);
|
artifact=GetImageArtifact(image,"filter:kaiser-beta");
|
if (artifact != (const char *) NULL)
|
value=StringToDouble(artifact,(char **) NULL);
|
artifact=GetImageArtifact(image,"filter:kaiser-alpha");
|
if (artifact != (const char *) NULL)
|
value=StringToDouble(artifact,(char **) NULL)*MagickPI;
|
/* Define coefficents for Kaiser Windowing Function */
|
resize_filter->coefficient[0]=value; /* alpha */
|
resize_filter->coefficient[1]=PerceptibleReciprocal(I0(value));
|
/* normalization */
|
}
|
|
/* Support Overrides */
|
artifact=GetImageArtifact(image,"filter:lobes");
|
if (artifact != (const char *) NULL)
|
{
|
ssize_t
|
lobes;
|
|
lobes=(ssize_t) StringToLong(artifact);
|
if (lobes < 1)
|
lobes=1;
|
resize_filter->support=(double) lobes;
|
}
|
if (resize_filter->filter == Jinc)
|
{
|
/*
|
Convert a Jinc function lobes value to a real support value.
|
*/
|
if (resize_filter->support > 16)
|
resize_filter->support=jinc_zeros[15]; /* largest entry in table */
|
else
|
resize_filter->support=jinc_zeros[((long) resize_filter->support)-1];
|
/*
|
Blur this filter so support is a integer value (lobes dependant).
|
*/
|
if (filter_type == LanczosRadiusFilter)
|
resize_filter->blur*=floor(resize_filter->support)/
|
resize_filter->support;
|
}
|
/*
|
Expert blur override.
|
*/
|
artifact=GetImageArtifact(image,"filter:blur");
|
if (artifact != (const char *) NULL)
|
resize_filter->blur*=StringToDouble(artifact,(char **) NULL);
|
if (resize_filter->blur < MagickEpsilon)
|
resize_filter->blur=(double) MagickEpsilon;
|
/*
|
Expert override of the support setting.
|
*/
|
artifact=GetImageArtifact(image,"filter:support");
|
if (artifact != (const char *) NULL)
|
resize_filter->support=fabs(StringToDouble(artifact,(char **) NULL));
|
/*
|
Scale windowing function separately to the support 'clipping' window
|
that calling operator is planning to actually use. (Expert override)
|
*/
|
resize_filter->window_support=resize_filter->support; /* default */
|
artifact=GetImageArtifact(image,"filter:win-support");
|
if (artifact != (const char *) NULL)
|
resize_filter->window_support=fabs(StringToDouble(artifact,(char **) NULL));
|
/*
|
Adjust window function scaling to match windowing support for weighting
|
function. This avoids a division on every filter call.
|
*/
|
resize_filter->scale/=resize_filter->window_support;
|
/*
|
* Set Cubic Spline B,C values, calculate Cubic coefficients.
|
*/
|
B=0.0;
|
C=0.0;
|
if ((resize_filter->filter == CubicBC) ||
|
(resize_filter->window == CubicBC) )
|
{
|
B=filters[filter_type].B;
|
C=filters[filter_type].C;
|
if (filters[window_type].function == CubicBC)
|
{
|
B=filters[window_type].B;
|
C=filters[window_type].C;
|
}
|
artifact=GetImageArtifact(image,"filter:b");
|
if (artifact != (const char *) NULL)
|
{
|
B=StringToDouble(artifact,(char **) NULL);
|
C=(1.0-B)/2.0; /* Calculate C to get a Keys cubic filter. */
|
artifact=GetImageArtifact(image,"filter:c"); /* user C override */
|
if (artifact != (const char *) NULL)
|
C=StringToDouble(artifact,(char **) NULL);
|
}
|
else
|
{
|
artifact=GetImageArtifact(image,"filter:c");
|
if (artifact != (const char *) NULL)
|
{
|
C=StringToDouble(artifact,(char **) NULL);
|
B=1.0-2.0*C; /* Calculate B to get a Keys cubic filter. */
|
}
|
}
|
{
|
const double
|
twoB = B+B;
|
|
/*
|
Convert B,C values into Cubic Coefficents. See CubicBC().
|
*/
|
resize_filter->coefficient[0]=1.0-(1.0/3.0)*B;
|
resize_filter->coefficient[1]=-3.0+twoB+C;
|
resize_filter->coefficient[2]=2.0-1.5*B-C;
|
resize_filter->coefficient[3]=(4.0/3.0)*B+4.0*C;
|
resize_filter->coefficient[4]=-8.0*C-twoB;
|
resize_filter->coefficient[5]=B+5.0*C;
|
resize_filter->coefficient[6]=(-1.0/6.0)*B-C;
|
}
|
}
|
|
/*
|
Expert Option Request for verbose details of the resulting filter.
|
*/
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp master
|
{
|
#endif
|
if (IsStringTrue(GetImageArtifact(image,"filter:verbose")) != MagickFalse)
|
{
|
double
|
support,
|
x;
|
|
/*
|
Set the weighting function properly when the weighting function
|
may not exactly match the filter of the same name. EG: a Point
|
filter is really uses a Box weighting function with a different
|
support than is typically used.
|
*/
|
if (resize_filter->filter == Box) filter_type=BoxFilter;
|
if (resize_filter->filter == Sinc) filter_type=SincFilter;
|
if (resize_filter->filter == SincFast) filter_type=SincFastFilter;
|
if (resize_filter->filter == Jinc) filter_type=JincFilter;
|
if (resize_filter->filter == CubicBC) filter_type=CubicFilter;
|
if (resize_filter->window == Box) window_type=BoxFilter;
|
if (resize_filter->window == Sinc) window_type=SincFilter;
|
if (resize_filter->window == SincFast) window_type=SincFastFilter;
|
if (resize_filter->window == Jinc) window_type=JincFilter;
|
if (resize_filter->window == CubicBC) window_type=CubicFilter;
|
/*
|
Report Filter Details.
|
*/
|
support=GetResizeFilterSupport(resize_filter); /* practical_support */
|
(void) FormatLocaleFile(stdout,
|
"# Resampling Filter (for graphing)\n#\n");
|
(void) FormatLocaleFile(stdout,"# filter = %s\n",
|
CommandOptionToMnemonic(MagickFilterOptions,filter_type));
|
(void) FormatLocaleFile(stdout,"# window = %s\n",
|
CommandOptionToMnemonic(MagickFilterOptions,window_type));
|
(void) FormatLocaleFile(stdout,"# support = %.*g\n",
|
GetMagickPrecision(),(double) resize_filter->support);
|
(void) FormatLocaleFile(stdout,"# window-support = %.*g\n",
|
GetMagickPrecision(),(double) resize_filter->window_support);
|
(void) FormatLocaleFile(stdout,"# scale-blur = %.*g\n",
|
GetMagickPrecision(),(double) resize_filter->blur);
|
if ((filter_type == GaussianFilter) || (window_type == GaussianFilter))
|
(void) FormatLocaleFile(stdout,"# gaussian-sigma = %.*g\n",
|
GetMagickPrecision(),(double) resize_filter->coefficient[0]);
|
if ( filter_type == KaiserFilter || window_type == KaiserFilter )
|
(void) FormatLocaleFile(stdout,"# kaiser-beta = %.*g\n",
|
GetMagickPrecision(),(double) resize_filter->coefficient[0]);
|
(void) FormatLocaleFile(stdout,"# practical-support = %.*g\n",
|
GetMagickPrecision(), (double) support);
|
if ((filter_type == CubicFilter) || (window_type == CubicFilter))
|
(void) FormatLocaleFile(stdout,"# B,C = %.*g,%.*g\n",
|
GetMagickPrecision(),(double) B,GetMagickPrecision(),(double) C);
|
(void) FormatLocaleFile(stdout,"\n");
|
/*
|
Output values of resulting filter graph -- for graphing filter result.
|
*/
|
for (x=0.0; x <= support; x+=0.01f)
|
(void) FormatLocaleFile(stdout,"%5.2lf\t%.*g\n",x,
|
GetMagickPrecision(),(double)
|
GetResizeFilterWeight(resize_filter,x));
|
/*
|
A final value so gnuplot can graph the 'stop' properly.
|
*/
|
(void) FormatLocaleFile(stdout,"%5.2lf\t%.*g\n",support,
|
GetMagickPrecision(),0.0);
|
}
|
/* Output the above once only for each image - remove setting */
|
(void) DeleteImageArtifact((Image *) image,"filter:verbose");
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
}
|
#endif
|
return(resize_filter);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% A d a p t i v e R e s i z e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% AdaptiveResizeImage() adaptively resize image with pixel resampling.
|
%
|
% This is shortcut function for a fast interpolative resize using mesh
|
% interpolation. It works well for small resizes of less than +/- 50%
|
% of the original image size. For larger resizing on images a full
|
% filtered and slower resize function should be used instead.
|
%
|
% The format of the AdaptiveResizeImage method is:
|
%
|
% Image *AdaptiveResizeImage(const Image *image,const size_t columns,
|
% const size_t rows,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the resized image.
|
%
|
% o rows: the number of rows in the resized image.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *AdaptiveResizeImage(const Image *image,
|
const size_t columns,const size_t rows,ExceptionInfo *exception)
|
{
|
Image
|
*resize_image;
|
|
resize_image=InterpolativeResizeImage(image,columns,rows,MeshInterpolatePixel,
|
exception);
|
return(resize_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
+ B e s s e l O r d e r O n e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% BesselOrderOne() computes the Bessel function of x of the first kind of
|
% order 0. This is used to create the Jinc() filter function below.
|
%
|
% Reduce x to |x| since j1(x)= -j1(-x), and for x in (0,8]
|
%
|
% j1(x) = x*j1(x);
|
%
|
% For x in (8,inf)
|
%
|
% j1(x) = sqrt(2/(pi*x))*(p1(x)*cos(x1)-q1(x)*sin(x1))
|
%
|
% where x1 = x-3*pi/4. Compute sin(x1) and cos(x1) as follow:
|
%
|
% cos(x1) = cos(x)cos(3pi/4)+sin(x)sin(3pi/4)
|
% = 1/sqrt(2) * (sin(x) - cos(x))
|
% sin(x1) = sin(x)cos(3pi/4)-cos(x)sin(3pi/4)
|
% = -1/sqrt(2) * (sin(x) + cos(x))
|
%
|
% The format of the BesselOrderOne method is:
|
%
|
% double BesselOrderOne(double x)
|
%
|
% A description of each parameter follows:
|
%
|
% o x: double value.
|
%
|
*/
|
|
#undef I0
|
static double I0(double x)
|
{
|
double
|
sum,
|
t,
|
y;
|
|
register ssize_t
|
i;
|
|
/*
|
Zeroth order Bessel function of the first kind.
|
*/
|
sum=1.0;
|
y=x*x/4.0;
|
t=y;
|
for (i=2; t > MagickEpsilon; i++)
|
{
|
sum+=t;
|
t*=y/((double) i*i);
|
}
|
return(sum);
|
}
|
|
#undef J1
|
static double J1(double x)
|
{
|
double
|
p,
|
q;
|
|
register ssize_t
|
i;
|
|
static const double
|
Pone[] =
|
{
|
0.581199354001606143928050809e+21,
|
-0.6672106568924916298020941484e+20,
|
0.2316433580634002297931815435e+19,
|
-0.3588817569910106050743641413e+17,
|
0.2908795263834775409737601689e+15,
|
-0.1322983480332126453125473247e+13,
|
0.3413234182301700539091292655e+10,
|
-0.4695753530642995859767162166e+7,
|
0.270112271089232341485679099e+4
|
},
|
Qone[] =
|
{
|
0.11623987080032122878585294e+22,
|
0.1185770712190320999837113348e+20,
|
0.6092061398917521746105196863e+17,
|
0.2081661221307607351240184229e+15,
|
0.5243710262167649715406728642e+12,
|
0.1013863514358673989967045588e+10,
|
0.1501793594998585505921097578e+7,
|
0.1606931573481487801970916749e+4,
|
0.1e+1
|
};
|
|
p=Pone[8];
|
q=Qone[8];
|
for (i=7; i >= 0; i--)
|
{
|
p=p*x*x+Pone[i];
|
q=q*x*x+Qone[i];
|
}
|
return(p/q);
|
}
|
|
#undef P1
|
static double P1(double x)
|
{
|
double
|
p,
|
q;
|
|
register ssize_t
|
i;
|
|
static const double
|
Pone[] =
|
{
|
0.352246649133679798341724373e+5,
|
0.62758845247161281269005675e+5,
|
0.313539631109159574238669888e+5,
|
0.49854832060594338434500455e+4,
|
0.2111529182853962382105718e+3,
|
0.12571716929145341558495e+1
|
},
|
Qone[] =
|
{
|
0.352246649133679798068390431e+5,
|
0.626943469593560511888833731e+5,
|
0.312404063819041039923015703e+5,
|
0.4930396490181088979386097e+4,
|
0.2030775189134759322293574e+3,
|
0.1e+1
|
};
|
|
p=Pone[5];
|
q=Qone[5];
|
for (i=4; i >= 0; i--)
|
{
|
p=p*(8.0/x)*(8.0/x)+Pone[i];
|
q=q*(8.0/x)*(8.0/x)+Qone[i];
|
}
|
return(p/q);
|
}
|
|
#undef Q1
|
static double Q1(double x)
|
{
|
double
|
p,
|
q;
|
|
register ssize_t
|
i;
|
|
static const double
|
Pone[] =
|
{
|
0.3511751914303552822533318e+3,
|
0.7210391804904475039280863e+3,
|
0.4259873011654442389886993e+3,
|
0.831898957673850827325226e+2,
|
0.45681716295512267064405e+1,
|
0.3532840052740123642735e-1
|
},
|
Qone[] =
|
{
|
0.74917374171809127714519505e+4,
|
0.154141773392650970499848051e+5,
|
0.91522317015169922705904727e+4,
|
0.18111867005523513506724158e+4,
|
0.1038187585462133728776636e+3,
|
0.1e+1
|
};
|
|
p=Pone[5];
|
q=Qone[5];
|
for (i=4; i >= 0; i--)
|
{
|
p=p*(8.0/x)*(8.0/x)+Pone[i];
|
q=q*(8.0/x)*(8.0/x)+Qone[i];
|
}
|
return(p/q);
|
}
|
|
static double BesselOrderOne(double x)
|
{
|
double
|
p,
|
q;
|
|
if (x == 0.0)
|
return(0.0);
|
p=x;
|
if (x < 0.0)
|
x=(-x);
|
if (x < 8.0)
|
return(p*J1(x));
|
q=sqrt((double) (2.0/(MagickPI*x)))*(P1(x)*(1.0/sqrt(2.0)*(sin((double) x)-
|
cos((double) x)))-8.0/x*Q1(x)*(-1.0/sqrt(2.0)*(sin((double) x)+
|
cos((double) x))));
|
if (p < 0.0)
|
q=(-q);
|
return(q);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
+ D e s t r o y R e s i z e F i l t e r %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% DestroyResizeFilter() destroy the resize filter.
|
%
|
% The format of the DestroyResizeFilter method is:
|
%
|
% ResizeFilter *DestroyResizeFilter(ResizeFilter *resize_filter)
|
%
|
% A description of each parameter follows:
|
%
|
% o resize_filter: the resize filter.
|
%
|
*/
|
MagickPrivate ResizeFilter *DestroyResizeFilter(ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
resize_filter->signature=(~MagickCoreSignature);
|
resize_filter=(ResizeFilter *) RelinquishMagickMemory(resize_filter);
|
return(resize_filter);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
+ G e t R e s i z e F i l t e r S u p p o r t %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% GetResizeFilterSupport() return the current support window size for this
|
% filter. Note that this may have been enlarged by filter:blur factor.
|
%
|
% The format of the GetResizeFilterSupport method is:
|
%
|
% double GetResizeFilterSupport(const ResizeFilter *resize_filter)
|
%
|
% A description of each parameter follows:
|
%
|
% o filter: Image filter to use.
|
%
|
*/
|
|
MagickPrivate double *GetResizeFilterCoefficient(
|
const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return((double *) resize_filter->coefficient);
|
}
|
|
MagickPrivate double GetResizeFilterBlur(const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->blur);
|
}
|
|
MagickPrivate double GetResizeFilterScale(const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->scale);
|
}
|
|
MagickPrivate double GetResizeFilterWindowSupport(
|
const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->window_support);
|
}
|
|
MagickPrivate ResizeWeightingFunctionType GetResizeFilterWeightingType(
|
const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->filterWeightingType);
|
}
|
|
MagickPrivate ResizeWeightingFunctionType GetResizeFilterWindowWeightingType(
|
const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->windowWeightingType);
|
}
|
|
MagickPrivate double GetResizeFilterSupport(const ResizeFilter *resize_filter)
|
{
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
return(resize_filter->support*resize_filter->blur);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
+ G e t R e s i z e F i l t e r W e i g h t %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% GetResizeFilterWeight evaluates the specified resize filter at the point x
|
% which usally lies between zero and the filters current 'support' and
|
% returns the weight of the filter function at that point.
|
%
|
% The format of the GetResizeFilterWeight method is:
|
%
|
% double GetResizeFilterWeight(const ResizeFilter *resize_filter,
|
% const double x)
|
%
|
% A description of each parameter follows:
|
%
|
% o filter: the filter type.
|
%
|
% o x: the point.
|
%
|
*/
|
MagickPrivate double GetResizeFilterWeight(const ResizeFilter *resize_filter,
|
const double x)
|
{
|
double
|
scale,
|
weight,
|
x_blur;
|
|
/*
|
Windowing function - scale the weighting filter by this amount.
|
*/
|
assert(resize_filter != (ResizeFilter *) NULL);
|
assert(resize_filter->signature == MagickCoreSignature);
|
x_blur=fabs((double) x)/resize_filter->blur; /* X offset with blur scaling */
|
if ((resize_filter->window_support < MagickEpsilon) ||
|
(resize_filter->window == Box))
|
scale=1.0; /* Point or Box Filter -- avoid division by zero */
|
else
|
{
|
scale=resize_filter->scale;
|
scale=resize_filter->window(x_blur*scale,resize_filter);
|
}
|
weight=scale*resize_filter->filter(x_blur,resize_filter);
|
return(weight);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% I n t e r p o l a t i v e R e s i z e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% InterpolativeResizeImage() resizes an image using the specified
|
% interpolation method.
|
%
|
% The format of the InterpolativeResizeImage method is:
|
%
|
% Image *InterpolativeResizeImage(const Image *image,const size_t columns,
|
% const size_t rows,const PixelInterpolateMethod method,
|
% ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the resized image.
|
%
|
% o rows: the number of rows in the resized image.
|
%
|
% o method: the pixel interpolation method.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *InterpolativeResizeImage(const Image *image,
|
const size_t columns,const size_t rows,const PixelInterpolateMethod method,
|
ExceptionInfo *exception)
|
{
|
#define InterpolativeResizeImageTag "Resize/Image"
|
|
CacheView
|
*image_view,
|
*resize_view;
|
|
Image
|
*resize_image;
|
|
MagickBooleanType
|
status;
|
|
MagickOffsetType
|
progress;
|
|
PointInfo
|
scale;
|
|
ssize_t
|
y;
|
|
/*
|
Interpolatively resize image.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
if ((columns == 0) || (rows == 0))
|
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
|
if ((columns == image->columns) && (rows == image->rows))
|
return(CloneImage(image,0,0,MagickTrue,exception));
|
resize_image=CloneImage(image,columns,rows,MagickTrue,exception);
|
if (resize_image == (Image *) NULL)
|
return((Image *) NULL);
|
if (SetImageStorageClass(resize_image,DirectClass,exception) == MagickFalse)
|
{
|
resize_image=DestroyImage(resize_image);
|
return((Image *) NULL);
|
}
|
status=MagickTrue;
|
progress=0;
|
image_view=AcquireVirtualCacheView(image,exception);
|
resize_view=AcquireAuthenticCacheView(resize_image,exception);
|
scale.x=(double) image->columns/resize_image->columns;
|
scale.y=(double) image->rows/resize_image->rows;
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp parallel for schedule(static) shared(progress,status) \
|
magick_number_threads(image,resize_image,resize_image->rows,1)
|
#endif
|
for (y=0; y < (ssize_t) resize_image->rows; y++)
|
{
|
PointInfo
|
offset;
|
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
x;
|
|
if (status == MagickFalse)
|
continue;
|
q=QueueCacheViewAuthenticPixels(resize_view,0,y,resize_image->columns,1,
|
exception);
|
if (q == (Quantum *) NULL)
|
continue;
|
offset.y=((double) y+0.5)*scale.y-0.5;
|
for (x=0; x < (ssize_t) resize_image->columns; x++)
|
{
|
register ssize_t
|
i;
|
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel
|
channel;
|
|
PixelTrait
|
resize_traits,
|
traits;
|
|
channel=GetPixelChannelChannel(image,i);
|
traits=GetPixelChannelTraits(image,channel);
|
resize_traits=GetPixelChannelTraits(resize_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(resize_traits == UndefinedPixelTrait))
|
continue;
|
offset.x=((double) x+0.5)*scale.x-0.5;
|
status=InterpolatePixelChannels(image,image_view,resize_image,method,
|
offset.x,offset.y,q,exception);
|
if (status == MagickFalse)
|
break;
|
}
|
q+=GetPixelChannels(resize_image);
|
}
|
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
|
status=MagickFalse;
|
if (image->progress_monitor != (MagickProgressMonitor) NULL)
|
{
|
MagickBooleanType
|
proceed;
|
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp atomic
|
#endif
|
progress++;
|
proceed=SetImageProgress(image,InterpolativeResizeImageTag,progress,
|
image->rows);
|
if (proceed == MagickFalse)
|
status=MagickFalse;
|
}
|
}
|
resize_view=DestroyCacheView(resize_view);
|
image_view=DestroyCacheView(image_view);
|
if (status == MagickFalse)
|
resize_image=DestroyImage(resize_image);
|
return(resize_image);
|
}
|
#if defined(MAGICKCORE_LQR_DELEGATE)
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% L i q u i d R e s c a l e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% LiquidRescaleImage() rescales image with seam carving.
|
%
|
% The format of the LiquidRescaleImage method is:
|
%
|
% Image *LiquidRescaleImage(const Image *image,const size_t columns,
|
% const size_t rows,const double delta_x,const double rigidity,
|
% ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the rescaled image.
|
%
|
% o rows: the number of rows in the rescaled image.
|
%
|
% o delta_x: maximum seam transversal step (0 means straight seams).
|
%
|
% o rigidity: introduce a bias for non-straight seams (typically 0).
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *LiquidRescaleImage(const Image *image,const size_t columns,
|
const size_t rows,const double delta_x,const double rigidity,
|
ExceptionInfo *exception)
|
{
|
#define LiquidRescaleImageTag "Rescale/Image"
|
|
CacheView
|
*image_view,
|
*rescale_view;
|
|
gfloat
|
*packet,
|
*pixels;
|
|
Image
|
*rescale_image;
|
|
int
|
x_offset,
|
y_offset;
|
|
LqrCarver
|
*carver;
|
|
LqrRetVal
|
lqr_status;
|
|
MagickBooleanType
|
status;
|
|
MemoryInfo
|
*pixel_info;
|
|
register gfloat
|
*q;
|
|
ssize_t
|
y;
|
|
/*
|
Liquid rescale image.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
if ((columns == 0) || (rows == 0))
|
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
|
if ((columns == image->columns) && (rows == image->rows))
|
return(CloneImage(image,0,0,MagickTrue,exception));
|
if ((columns <= 2) || (rows <= 2))
|
return(ResizeImage(image,columns,rows,image->filter,exception));
|
pixel_info=AcquireVirtualMemory(image->columns,image->rows*MaxPixelChannels*
|
sizeof(*pixels));
|
if (pixel_info == (MemoryInfo *) NULL)
|
return((Image *) NULL);
|
pixels=(gfloat *) GetVirtualMemoryBlob(pixel_info);
|
status=MagickTrue;
|
q=pixels;
|
image_view=AcquireVirtualCacheView(image,exception);
|
for (y=0; y < (ssize_t) image->rows; y++)
|
{
|
register const Quantum
|
*magick_restrict p;
|
|
register ssize_t
|
x;
|
|
if (status == MagickFalse)
|
continue;
|
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
|
if (p == (const Quantum *) NULL)
|
{
|
status=MagickFalse;
|
continue;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
register ssize_t
|
i;
|
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
*q++=QuantumScale*p[i];
|
p+=GetPixelChannels(image);
|
}
|
}
|
image_view=DestroyCacheView(image_view);
|
carver=lqr_carver_new_ext(pixels,(int) image->columns,(int) image->rows,
|
(int) GetPixelChannels(image),LQR_COLDEPTH_32F);
|
if (carver == (LqrCarver *) NULL)
|
{
|
pixel_info=RelinquishVirtualMemory(pixel_info);
|
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
|
}
|
lqr_carver_set_preserve_input_image(carver);
|
lqr_status=lqr_carver_init(carver,(int) delta_x,rigidity);
|
lqr_status=lqr_carver_resize(carver,(int) columns,(int) rows);
|
(void) lqr_status;
|
rescale_image=CloneImage(image,lqr_carver_get_width(carver),
|
lqr_carver_get_height(carver),MagickTrue,exception);
|
if (rescale_image == (Image *) NULL)
|
{
|
pixel_info=RelinquishVirtualMemory(pixel_info);
|
return((Image *) NULL);
|
}
|
if (SetImageStorageClass(rescale_image,DirectClass,exception) == MagickFalse)
|
{
|
pixel_info=RelinquishVirtualMemory(pixel_info);
|
rescale_image=DestroyImage(rescale_image);
|
return((Image *) NULL);
|
}
|
rescale_view=AcquireAuthenticCacheView(rescale_image,exception);
|
(void) lqr_carver_scan_reset(carver);
|
while (lqr_carver_scan_ext(carver,&x_offset,&y_offset,(void **) &packet) != 0)
|
{
|
register Quantum
|
*magick_restrict p;
|
|
register ssize_t
|
i;
|
|
p=QueueCacheViewAuthenticPixels(rescale_view,x_offset,y_offset,1,1,
|
exception);
|
if (p == (Quantum *) NULL)
|
break;
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel
|
channel;
|
|
PixelTrait
|
rescale_traits,
|
traits;
|
|
channel=GetPixelChannelChannel(image,i);
|
traits=GetPixelChannelTraits(image,channel);
|
rescale_traits=GetPixelChannelTraits(rescale_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(rescale_traits == UndefinedPixelTrait))
|
continue;
|
SetPixelChannel(rescale_image,channel,ClampToQuantum(QuantumRange*
|
packet[i]),p);
|
}
|
if (SyncCacheViewAuthenticPixels(rescale_view,exception) == MagickFalse)
|
break;
|
}
|
rescale_view=DestroyCacheView(rescale_view);
|
pixel_info=RelinquishVirtualMemory(pixel_info);
|
lqr_carver_destroy(carver);
|
return(rescale_image);
|
}
|
#else
|
MagickExport Image *LiquidRescaleImage(const Image *image,
|
const size_t magick_unused(columns),const size_t magick_unused(rows),
|
const double magick_unused(delta_x),const double magick_unused(rigidity),
|
ExceptionInfo *exception)
|
{
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
(void) ThrowMagickException(exception,GetMagickModule(),MissingDelegateError,
|
"DelegateLibrarySupportNotBuiltIn","'%s' (LQR)",image->filename);
|
return((Image *) NULL);
|
}
|
#endif
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% M a g n i f y I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% MagnifyImage() doubles the size of the image with a pixel art scaling
|
% algorithm.
|
%
|
% The format of the MagnifyImage method is:
|
%
|
% Image *MagnifyImage(const Image *image,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *MagnifyImage(const Image *image,ExceptionInfo *exception)
|
{
|
#define MagnifyImageTag "Magnify/Image"
|
|
CacheView
|
*image_view,
|
*magnify_view;
|
|
Image
|
*magnify_image;
|
|
MagickBooleanType
|
status;
|
|
MagickOffsetType
|
progress;
|
|
ssize_t
|
y;
|
|
/*
|
Initialize magnified image attributes.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
magnify_image=CloneImage(image,2*image->columns,2*image->rows,MagickTrue,
|
exception);
|
if (magnify_image == (Image *) NULL)
|
return((Image *) NULL);
|
/*
|
Magnify image.
|
*/
|
status=MagickTrue;
|
progress=0;
|
image_view=AcquireVirtualCacheView(image,exception);
|
magnify_view=AcquireAuthenticCacheView(magnify_image,exception);
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp parallel for schedule(static) shared(progress,status) \
|
magick_number_threads(image,magnify_image,image->rows,1)
|
#endif
|
for (y=0; y < (ssize_t) image->rows; y++)
|
{
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
x;
|
|
if (status == MagickFalse)
|
continue;
|
q=QueueCacheViewAuthenticPixels(magnify_view,0,2*y,magnify_image->columns,2,
|
exception);
|
if (q == (Quantum *) NULL)
|
{
|
status=MagickFalse;
|
continue;
|
}
|
/*
|
Magnify this row of pixels.
|
*/
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
MagickRealType
|
intensity[9];
|
|
register const Quantum
|
*magick_restrict p;
|
|
register Quantum
|
*magick_restrict r;
|
|
register ssize_t
|
i;
|
|
size_t
|
channels;
|
|
p=GetCacheViewVirtualPixels(image_view,x-1,y-1,3,3,exception);
|
if (p == (const Quantum *) NULL)
|
{
|
status=MagickFalse;
|
continue;
|
}
|
channels=GetPixelChannels(image);
|
for (i=0; i < 9; i++)
|
intensity[i]=GetPixelIntensity(image,p+i*channels);
|
r=q;
|
if ((fabs(intensity[1]-intensity[7]) < MagickEpsilon) ||
|
(fabs(intensity[3]-intensity[5]) < MagickEpsilon))
|
{
|
/*
|
Clone center pixel.
|
*/
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image);
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image)*(magnify_image->columns-1);
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image);
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
}
|
else
|
{
|
/*
|
Selectively clone pixel.
|
*/
|
if (fabs(intensity[1]-intensity[3]) < MagickEpsilon)
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[3*channels+i];
|
else
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image);
|
if (fabs(intensity[1]-intensity[5]) < MagickEpsilon)
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[5*channels+i];
|
else
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image)*(magnify_image->columns-1);
|
if (fabs(intensity[3]-intensity[7]) < MagickEpsilon)
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[3*channels+i];
|
else
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
r+=GetPixelChannels(magnify_image);
|
if (fabs(intensity[5]-intensity[7]) < MagickEpsilon)
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[5*channels+i];
|
else
|
for (i=0; i < (ssize_t) channels; i++)
|
r[i]=p[4*channels+i];
|
}
|
q+=2*GetPixelChannels(magnify_image);
|
}
|
if (SyncCacheViewAuthenticPixels(magnify_view,exception) == MagickFalse)
|
status=MagickFalse;
|
if (image->progress_monitor != (MagickProgressMonitor) NULL)
|
{
|
MagickBooleanType
|
proceed;
|
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp atomic
|
#endif
|
progress++;
|
proceed=SetImageProgress(image,MagnifyImageTag,progress,image->rows);
|
if (proceed == MagickFalse)
|
status=MagickFalse;
|
}
|
}
|
magnify_view=DestroyCacheView(magnify_view);
|
image_view=DestroyCacheView(image_view);
|
if (status == MagickFalse)
|
magnify_image=DestroyImage(magnify_image);
|
return(magnify_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% M i n i f y I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% MinifyImage() is a convenience method that scales an image proportionally to
|
% half its size.
|
%
|
% The format of the MinifyImage method is:
|
%
|
% Image *MinifyImage(const Image *image,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *MinifyImage(const Image *image,ExceptionInfo *exception)
|
{
|
Image
|
*minify_image;
|
|
assert(image != (Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
minify_image=ResizeImage(image,image->columns/2,image->rows/2,SplineFilter,
|
exception);
|
return(minify_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% R e s a m p l e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% ResampleImage() resize image in terms of its pixel size, so that when
|
% displayed at the given resolution it will be the same size in terms of
|
% real world units as the original image at the original resolution.
|
%
|
% The format of the ResampleImage method is:
|
%
|
% Image *ResampleImage(Image *image,const double x_resolution,
|
% const double y_resolution,const FilterType filter,
|
% ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image to be resized to fit the given resolution.
|
%
|
% o x_resolution: the new image x resolution.
|
%
|
% o y_resolution: the new image y resolution.
|
%
|
% o filter: Image filter to use.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *ResampleImage(const Image *image,const double x_resolution,
|
const double y_resolution,const FilterType filter,ExceptionInfo *exception)
|
{
|
#define ResampleImageTag "Resample/Image"
|
|
Image
|
*resample_image;
|
|
size_t
|
height,
|
width;
|
|
/*
|
Initialize sampled image attributes.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
width=(size_t) (x_resolution*image->columns/(image->resolution.x == 0.0 ?
|
72.0 : image->resolution.x)+0.5);
|
height=(size_t) (y_resolution*image->rows/(image->resolution.y == 0.0 ?
|
72.0 : image->resolution.y)+0.5);
|
resample_image=ResizeImage(image,width,height,filter,exception);
|
if (resample_image != (Image *) NULL)
|
{
|
resample_image->resolution.x=x_resolution;
|
resample_image->resolution.y=y_resolution;
|
}
|
return(resample_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% R e s i z e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% ResizeImage() scales an image to the desired dimensions, using the given
|
% filter (see AcquireFilterInfo()).
|
%
|
% If an undefined filter is given the filter defaults to Mitchell for a
|
% colormapped image, a image with a matte channel, or if the image is
|
% enlarged. Otherwise the filter defaults to a Lanczos.
|
%
|
% ResizeImage() was inspired by Paul Heckbert's "zoom" program.
|
%
|
% The format of the ResizeImage method is:
|
%
|
% Image *ResizeImage(Image *image,const size_t columns,const size_t rows,
|
% const FilterType filter,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the scaled image.
|
%
|
% o rows: the number of rows in the scaled image.
|
%
|
% o filter: Image filter to use.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
|
typedef struct _ContributionInfo
|
{
|
double
|
weight;
|
|
ssize_t
|
pixel;
|
} ContributionInfo;
|
|
static ContributionInfo **DestroyContributionThreadSet(
|
ContributionInfo **contribution)
|
{
|
register ssize_t
|
i;
|
|
assert(contribution != (ContributionInfo **) NULL);
|
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
|
if (contribution[i] != (ContributionInfo *) NULL)
|
contribution[i]=(ContributionInfo *) RelinquishAlignedMemory(
|
contribution[i]);
|
contribution=(ContributionInfo **) RelinquishMagickMemory(contribution);
|
return(contribution);
|
}
|
|
static ContributionInfo **AcquireContributionThreadSet(const size_t count)
|
{
|
register ssize_t
|
i;
|
|
ContributionInfo
|
**contribution;
|
|
size_t
|
number_threads;
|
|
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
|
contribution=(ContributionInfo **) AcquireQuantumMemory(number_threads,
|
sizeof(*contribution));
|
if (contribution == (ContributionInfo **) NULL)
|
return((ContributionInfo **) NULL);
|
(void) memset(contribution,0,number_threads*sizeof(*contribution));
|
for (i=0; i < (ssize_t) number_threads; i++)
|
{
|
contribution[i]=(ContributionInfo *) MagickAssumeAligned(
|
AcquireAlignedMemory(count,sizeof(**contribution)));
|
if (contribution[i] == (ContributionInfo *) NULL)
|
return(DestroyContributionThreadSet(contribution));
|
}
|
return(contribution);
|
}
|
|
static MagickBooleanType HorizontalFilter(
|
const ResizeFilter *magick_restrict resize_filter,
|
const Image *magick_restrict image,Image *magick_restrict resize_image,
|
const double x_factor,const MagickSizeType span,
|
MagickOffsetType *magick_restrict progress,ExceptionInfo *exception)
|
{
|
#define ResizeImageTag "Resize/Image"
|
|
CacheView
|
*image_view,
|
*resize_view;
|
|
ClassType
|
storage_class;
|
|
ContributionInfo
|
**magick_restrict contributions;
|
|
MagickBooleanType
|
status;
|
|
double
|
scale,
|
support;
|
|
ssize_t
|
x;
|
|
/*
|
Apply filter to resize horizontally from image to resize image.
|
*/
|
scale=MagickMax(1.0/x_factor+MagickEpsilon,1.0);
|
support=scale*GetResizeFilterSupport(resize_filter);
|
storage_class=support > 0.5 ? DirectClass : image->storage_class;
|
if (SetImageStorageClass(resize_image,storage_class,exception) == MagickFalse)
|
return(MagickFalse);
|
if (support < 0.5)
|
{
|
/*
|
Support too small even for nearest neighbour: Reduce to point sampling.
|
*/
|
support=(double) 0.5;
|
scale=1.0;
|
}
|
contributions=AcquireContributionThreadSet((size_t) (2.0*support+3.0));
|
if (contributions == (ContributionInfo **) NULL)
|
{
|
(void) ThrowMagickException(exception,GetMagickModule(),
|
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
|
return(MagickFalse);
|
}
|
status=MagickTrue;
|
scale=PerceptibleReciprocal(scale);
|
image_view=AcquireVirtualCacheView(image,exception);
|
resize_view=AcquireAuthenticCacheView(resize_image,exception);
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp parallel for schedule(static) shared(progress,status) \
|
magick_number_threads(image,resize_image,resize_image->columns,1)
|
#endif
|
for (x=0; x < (ssize_t) resize_image->columns; x++)
|
{
|
const int
|
id = GetOpenMPThreadId();
|
|
double
|
bisect,
|
density;
|
|
register const Quantum
|
*magick_restrict p;
|
|
register ContributionInfo
|
*magick_restrict contribution;
|
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
y;
|
|
ssize_t
|
n,
|
start,
|
stop;
|
|
if (status == MagickFalse)
|
continue;
|
bisect=(double) (x+0.5)/x_factor+MagickEpsilon;
|
start=(ssize_t) MagickMax(bisect-support+0.5,0.0);
|
stop=(ssize_t) MagickMin(bisect+support+0.5,(double) image->columns);
|
density=0.0;
|
contribution=contributions[id];
|
for (n=0; n < (stop-start); n++)
|
{
|
contribution[n].pixel=start+n;
|
contribution[n].weight=GetResizeFilterWeight(resize_filter,scale*
|
((double) (start+n)-bisect+0.5));
|
density+=contribution[n].weight;
|
}
|
if (n == 0)
|
continue;
|
if ((density != 0.0) && (density != 1.0))
|
{
|
register ssize_t
|
i;
|
|
/*
|
Normalize.
|
*/
|
density=PerceptibleReciprocal(density);
|
for (i=0; i < n; i++)
|
contribution[i].weight*=density;
|
}
|
p=GetCacheViewVirtualPixels(image_view,contribution[0].pixel,0,(size_t)
|
(contribution[n-1].pixel-contribution[0].pixel+1),image->rows,exception);
|
q=QueueCacheViewAuthenticPixels(resize_view,x,0,1,resize_image->rows,
|
exception);
|
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
|
{
|
status=MagickFalse;
|
continue;
|
}
|
for (y=0; y < (ssize_t) resize_image->rows; y++)
|
{
|
register ssize_t
|
i;
|
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
double
|
alpha,
|
gamma,
|
pixel;
|
|
PixelChannel
|
channel;
|
|
PixelTrait
|
resize_traits,
|
traits;
|
|
register ssize_t
|
j;
|
|
ssize_t
|
k;
|
|
channel=GetPixelChannelChannel(image,i);
|
traits=GetPixelChannelTraits(image,channel);
|
resize_traits=GetPixelChannelTraits(resize_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(resize_traits == UndefinedPixelTrait))
|
continue;
|
if (((resize_traits & CopyPixelTrait) != 0) ||
|
(GetPixelWriteMask(resize_image,q) <= (QuantumRange/2)))
|
{
|
j=(ssize_t) (MagickMin(MagickMax(bisect,(double) start),(double)
|
stop-1.0)+0.5);
|
k=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
|
(contribution[j-start].pixel-contribution[0].pixel);
|
SetPixelChannel(resize_image,channel,p[k*GetPixelChannels(image)+i],
|
q);
|
continue;
|
}
|
pixel=0.0;
|
if ((resize_traits & BlendPixelTrait) == 0)
|
{
|
/*
|
No alpha blending.
|
*/
|
for (j=0; j < n; j++)
|
{
|
k=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
|
(contribution[j].pixel-contribution[0].pixel);
|
alpha=contribution[j].weight;
|
pixel+=alpha*p[k*GetPixelChannels(image)+i];
|
}
|
SetPixelChannel(resize_image,channel,ClampToQuantum(pixel),q);
|
continue;
|
}
|
/*
|
Alpha blending.
|
*/
|
gamma=0.0;
|
for (j=0; j < n; j++)
|
{
|
k=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
|
(contribution[j].pixel-contribution[0].pixel);
|
alpha=contribution[j].weight*QuantumScale*
|
GetPixelAlpha(image,p+k*GetPixelChannels(image));
|
pixel+=alpha*p[k*GetPixelChannels(image)+i];
|
gamma+=alpha;
|
}
|
gamma=PerceptibleReciprocal(gamma);
|
SetPixelChannel(resize_image,channel,ClampToQuantum(gamma*pixel),q);
|
}
|
q+=GetPixelChannels(resize_image);
|
}
|
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
|
status=MagickFalse;
|
if (image->progress_monitor != (MagickProgressMonitor) NULL)
|
{
|
MagickBooleanType
|
proceed;
|
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp atomic
|
#endif
|
(*progress)++;
|
proceed=SetImageProgress(image,ResizeImageTag,*progress,span);
|
if (proceed == MagickFalse)
|
status=MagickFalse;
|
}
|
}
|
resize_view=DestroyCacheView(resize_view);
|
image_view=DestroyCacheView(image_view);
|
contributions=DestroyContributionThreadSet(contributions);
|
return(status);
|
}
|
|
static MagickBooleanType VerticalFilter(
|
const ResizeFilter *magick_restrict resize_filter,
|
const Image *magick_restrict image,Image *magick_restrict resize_image,
|
const double y_factor,const MagickSizeType span,
|
MagickOffsetType *magick_restrict progress,ExceptionInfo *exception)
|
{
|
CacheView
|
*image_view,
|
*resize_view;
|
|
ClassType
|
storage_class;
|
|
ContributionInfo
|
**magick_restrict contributions;
|
|
double
|
scale,
|
support;
|
|
MagickBooleanType
|
status;
|
|
ssize_t
|
y;
|
|
/*
|
Apply filter to resize vertically from image to resize image.
|
*/
|
scale=MagickMax(1.0/y_factor+MagickEpsilon,1.0);
|
support=scale*GetResizeFilterSupport(resize_filter);
|
storage_class=support > 0.5 ? DirectClass : image->storage_class;
|
if (SetImageStorageClass(resize_image,storage_class,exception) == MagickFalse)
|
return(MagickFalse);
|
if (support < 0.5)
|
{
|
/*
|
Support too small even for nearest neighbour: Reduce to point sampling.
|
*/
|
support=(double) 0.5;
|
scale=1.0;
|
}
|
contributions=AcquireContributionThreadSet((size_t) (2.0*support+3.0));
|
if (contributions == (ContributionInfo **) NULL)
|
{
|
(void) ThrowMagickException(exception,GetMagickModule(),
|
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
|
return(MagickFalse);
|
}
|
status=MagickTrue;
|
scale=PerceptibleReciprocal(scale);
|
image_view=AcquireVirtualCacheView(image,exception);
|
resize_view=AcquireAuthenticCacheView(resize_image,exception);
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp parallel for schedule(static) shared(progress,status) \
|
magick_number_threads(image,resize_image,resize_image->rows,1)
|
#endif
|
for (y=0; y < (ssize_t) resize_image->rows; y++)
|
{
|
const int
|
id = GetOpenMPThreadId();
|
|
double
|
bisect,
|
density;
|
|
register const Quantum
|
*magick_restrict p;
|
|
register ContributionInfo
|
*magick_restrict contribution;
|
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
x;
|
|
ssize_t
|
n,
|
start,
|
stop;
|
|
if (status == MagickFalse)
|
continue;
|
bisect=(double) (y+0.5)/y_factor+MagickEpsilon;
|
start=(ssize_t) MagickMax(bisect-support+0.5,0.0);
|
stop=(ssize_t) MagickMin(bisect+support+0.5,(double) image->rows);
|
density=0.0;
|
contribution=contributions[id];
|
for (n=0; n < (stop-start); n++)
|
{
|
contribution[n].pixel=start+n;
|
contribution[n].weight=GetResizeFilterWeight(resize_filter,scale*
|
((double) (start+n)-bisect+0.5));
|
density+=contribution[n].weight;
|
}
|
if (n == 0)
|
continue;
|
if ((density != 0.0) && (density != 1.0))
|
{
|
register ssize_t
|
i;
|
|
/*
|
Normalize.
|
*/
|
density=PerceptibleReciprocal(density);
|
for (i=0; i < n; i++)
|
contribution[i].weight*=density;
|
}
|
p=GetCacheViewVirtualPixels(image_view,0,contribution[0].pixel,
|
image->columns,(size_t) (contribution[n-1].pixel-contribution[0].pixel+1),
|
exception);
|
q=QueueCacheViewAuthenticPixels(resize_view,0,y,resize_image->columns,1,
|
exception);
|
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
|
{
|
status=MagickFalse;
|
continue;
|
}
|
for (x=0; x < (ssize_t) resize_image->columns; x++)
|
{
|
register ssize_t
|
i;
|
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
double
|
alpha,
|
gamma,
|
pixel;
|
|
PixelChannel
|
channel;
|
|
PixelTrait
|
resize_traits,
|
traits;
|
|
register ssize_t
|
j;
|
|
ssize_t
|
k;
|
|
channel=GetPixelChannelChannel(image,i);
|
traits=GetPixelChannelTraits(image,channel);
|
resize_traits=GetPixelChannelTraits(resize_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(resize_traits == UndefinedPixelTrait))
|
continue;
|
if (((resize_traits & CopyPixelTrait) != 0) ||
|
(GetPixelWriteMask(resize_image,q) <= (QuantumRange/2)))
|
{
|
j=(ssize_t) (MagickMin(MagickMax(bisect,(double) start),(double)
|
stop-1.0)+0.5);
|
k=(ssize_t) ((contribution[j-start].pixel-contribution[0].pixel)*
|
image->columns+x);
|
SetPixelChannel(resize_image,channel,p[k*GetPixelChannels(image)+i],
|
q);
|
continue;
|
}
|
pixel=0.0;
|
if ((resize_traits & BlendPixelTrait) == 0)
|
{
|
/*
|
No alpha blending.
|
*/
|
for (j=0; j < n; j++)
|
{
|
k=(ssize_t) ((contribution[j].pixel-contribution[0].pixel)*
|
image->columns+x);
|
alpha=contribution[j].weight;
|
pixel+=alpha*p[k*GetPixelChannels(image)+i];
|
}
|
SetPixelChannel(resize_image,channel,ClampToQuantum(pixel),q);
|
continue;
|
}
|
gamma=0.0;
|
for (j=0; j < n; j++)
|
{
|
k=(ssize_t) ((contribution[j].pixel-contribution[0].pixel)*
|
image->columns+x);
|
alpha=contribution[j].weight*QuantumScale*GetPixelAlpha(image,p+k*
|
GetPixelChannels(image));
|
pixel+=alpha*p[k*GetPixelChannels(image)+i];
|
gamma+=alpha;
|
}
|
gamma=PerceptibleReciprocal(gamma);
|
SetPixelChannel(resize_image,channel,ClampToQuantum(gamma*pixel),q);
|
}
|
q+=GetPixelChannels(resize_image);
|
}
|
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
|
status=MagickFalse;
|
if (image->progress_monitor != (MagickProgressMonitor) NULL)
|
{
|
MagickBooleanType
|
proceed;
|
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp atomic
|
#endif
|
(*progress)++;
|
proceed=SetImageProgress(image,ResizeImageTag,*progress,span);
|
if (proceed == MagickFalse)
|
status=MagickFalse;
|
}
|
}
|
resize_view=DestroyCacheView(resize_view);
|
image_view=DestroyCacheView(image_view);
|
contributions=DestroyContributionThreadSet(contributions);
|
return(status);
|
}
|
|
MagickExport Image *ResizeImage(const Image *image,const size_t columns,
|
const size_t rows,const FilterType filter,ExceptionInfo *exception)
|
{
|
double
|
x_factor,
|
y_factor;
|
|
FilterType
|
filter_type;
|
|
Image
|
*filter_image,
|
*resize_image;
|
|
MagickOffsetType
|
offset;
|
|
MagickSizeType
|
span;
|
|
MagickStatusType
|
status;
|
|
ResizeFilter
|
*resize_filter;
|
|
/*
|
Acquire resize image.
|
*/
|
assert(image != (Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
if ((columns == 0) || (rows == 0))
|
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
|
if ((columns == image->columns) && (rows == image->rows) &&
|
(filter == UndefinedFilter))
|
return(CloneImage(image,0,0,MagickTrue,exception));
|
/*
|
Acquire resize filter.
|
*/
|
x_factor=(double) columns/(double) image->columns;
|
y_factor=(double) rows/(double) image->rows;
|
filter_type=LanczosFilter;
|
if (filter != UndefinedFilter)
|
filter_type=filter;
|
else
|
if ((x_factor == 1.0) && (y_factor == 1.0))
|
filter_type=PointFilter;
|
else
|
if ((image->storage_class == PseudoClass) ||
|
(image->alpha_trait != UndefinedPixelTrait) ||
|
((x_factor*y_factor) > 1.0))
|
filter_type=MitchellFilter;
|
resize_filter=AcquireResizeFilter(image,filter_type,MagickFalse,exception);
|
#if defined(MAGICKCORE_OPENCL_SUPPORT)
|
resize_image=AccelerateResizeImage(image,columns,rows,resize_filter,
|
exception);
|
if (resize_image != (Image *) NULL)
|
{
|
resize_filter=DestroyResizeFilter(resize_filter);
|
return(resize_image);
|
}
|
#endif
|
resize_image=CloneImage(image,columns,rows,MagickTrue,exception);
|
if (resize_image == (Image *) NULL)
|
{
|
resize_filter=DestroyResizeFilter(resize_filter);
|
return(resize_image);
|
}
|
if (x_factor > y_factor)
|
filter_image=CloneImage(image,columns,image->rows,MagickTrue,exception);
|
else
|
filter_image=CloneImage(image,image->columns,rows,MagickTrue,exception);
|
if (filter_image == (Image *) NULL)
|
{
|
resize_filter=DestroyResizeFilter(resize_filter);
|
return(DestroyImage(resize_image));
|
}
|
/*
|
Resize image.
|
*/
|
offset=0;
|
if (x_factor > y_factor)
|
{
|
span=(MagickSizeType) (filter_image->columns+rows);
|
status=HorizontalFilter(resize_filter,image,filter_image,x_factor,span,
|
&offset,exception);
|
status&=VerticalFilter(resize_filter,filter_image,resize_image,y_factor,
|
span,&offset,exception);
|
}
|
else
|
{
|
span=(MagickSizeType) (filter_image->rows+columns);
|
status=VerticalFilter(resize_filter,image,filter_image,y_factor,span,
|
&offset,exception);
|
status&=HorizontalFilter(resize_filter,filter_image,resize_image,x_factor,
|
span,&offset,exception);
|
}
|
/*
|
Free resources.
|
*/
|
filter_image=DestroyImage(filter_image);
|
resize_filter=DestroyResizeFilter(resize_filter);
|
if (status == MagickFalse)
|
{
|
resize_image=DestroyImage(resize_image);
|
return((Image *) NULL);
|
}
|
resize_image->type=image->type;
|
return(resize_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% S a m p l e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% SampleImage() scales an image to the desired dimensions with pixel
|
% sampling. Unlike other scaling methods, this method does not introduce
|
% any additional color into the scaled image.
|
%
|
% The format of the SampleImage method is:
|
%
|
% Image *SampleImage(const Image *image,const size_t columns,
|
% const size_t rows,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the sampled image.
|
%
|
% o rows: the number of rows in the sampled image.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *SampleImage(const Image *image,const size_t columns,
|
const size_t rows,ExceptionInfo *exception)
|
{
|
#define SampleImageTag "Sample/Image"
|
|
CacheView
|
*image_view,
|
*sample_view;
|
|
Image
|
*sample_image;
|
|
MagickBooleanType
|
status;
|
|
MagickOffsetType
|
progress;
|
|
register ssize_t
|
x1;
|
|
ssize_t
|
*x_offset,
|
y;
|
|
PointInfo
|
sample_offset;
|
|
/*
|
Initialize sampled image attributes.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
if ((columns == 0) || (rows == 0))
|
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
|
if ((columns == image->columns) && (rows == image->rows))
|
return(CloneImage(image,0,0,MagickTrue,exception));
|
sample_image=CloneImage(image,columns,rows,MagickTrue,exception);
|
if (sample_image == (Image *) NULL)
|
return((Image *) NULL);
|
/*
|
Set the sampling offset, default is in the mid-point of sample regions.
|
*/
|
sample_offset.x=sample_offset.y=0.5-MagickEpsilon;
|
{
|
const char
|
*value;
|
|
value=GetImageArtifact(image,"sample:offset");
|
if (value != (char *) NULL)
|
{
|
GeometryInfo
|
geometry_info;
|
|
MagickStatusType
|
flags;
|
|
(void) ParseGeometry(value,&geometry_info);
|
flags=ParseGeometry(value,&geometry_info);
|
sample_offset.x=sample_offset.y=geometry_info.rho/100.0-MagickEpsilon;
|
if ((flags & SigmaValue) != 0)
|
sample_offset.y=geometry_info.sigma/100.0-MagickEpsilon;
|
}
|
}
|
/*
|
Allocate scan line buffer and column offset buffers.
|
*/
|
x_offset=(ssize_t *) AcquireQuantumMemory((size_t) sample_image->columns,
|
sizeof(*x_offset));
|
if (x_offset == (ssize_t *) NULL)
|
{
|
sample_image=DestroyImage(sample_image);
|
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
|
}
|
for (x1=0; x1 < (ssize_t) sample_image->columns; x1++)
|
x_offset[x1]=(ssize_t) ((((double) x1+sample_offset.x)*image->columns)/
|
sample_image->columns);
|
/*
|
Sample each row.
|
*/
|
status=MagickTrue;
|
progress=0;
|
image_view=AcquireVirtualCacheView(image,exception);
|
sample_view=AcquireAuthenticCacheView(sample_image,exception);
|
#if defined(MAGICKCORE_OPENMP_SUPPORT)
|
#pragma omp parallel for schedule(static) shared(status) \
|
magick_number_threads(image,sample_image,sample_image->rows,1)
|
#endif
|
for (y=0; y < (ssize_t) sample_image->rows; y++)
|
{
|
register const Quantum
|
*magick_restrict p;
|
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
x;
|
|
ssize_t
|
y_offset;
|
|
if (status == MagickFalse)
|
continue;
|
y_offset=(ssize_t) ((((double) y+sample_offset.y)*image->rows)/
|
sample_image->rows);
|
p=GetCacheViewVirtualPixels(image_view,0,y_offset,image->columns,1,
|
exception);
|
q=QueueCacheViewAuthenticPixels(sample_view,0,y,sample_image->columns,1,
|
exception);
|
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
|
{
|
status=MagickFalse;
|
continue;
|
}
|
/*
|
Sample each column.
|
*/
|
for (x=0; x < (ssize_t) sample_image->columns; x++)
|
{
|
register ssize_t
|
i;
|
|
if (GetPixelWriteMask(sample_image,q) <= (QuantumRange/2))
|
{
|
q+=GetPixelChannels(sample_image);
|
continue;
|
}
|
for (i=0; i < (ssize_t) GetPixelChannels(sample_image); i++)
|
{
|
PixelChannel
|
channel;
|
|
PixelTrait
|
image_traits,
|
traits;
|
|
channel=GetPixelChannelChannel(sample_image,i);
|
traits=GetPixelChannelTraits(sample_image,channel);
|
image_traits=GetPixelChannelTraits(image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(image_traits == UndefinedPixelTrait))
|
continue;
|
SetPixelChannel(sample_image,channel,p[x_offset[x]*GetPixelChannels(
|
image)+i],q);
|
}
|
q+=GetPixelChannels(sample_image);
|
}
|
if (SyncCacheViewAuthenticPixels(sample_view,exception) == MagickFalse)
|
status=MagickFalse;
|
if (image->progress_monitor != (MagickProgressMonitor) NULL)
|
{
|
MagickBooleanType
|
proceed;
|
|
proceed=SetImageProgress(image,SampleImageTag,progress++,image->rows);
|
if (proceed == MagickFalse)
|
status=MagickFalse;
|
}
|
}
|
image_view=DestroyCacheView(image_view);
|
sample_view=DestroyCacheView(sample_view);
|
x_offset=(ssize_t *) RelinquishMagickMemory(x_offset);
|
sample_image->type=image->type;
|
if (status == MagickFalse)
|
sample_image=DestroyImage(sample_image);
|
return(sample_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% S c a l e I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% ScaleImage() changes the size of an image to the given dimensions.
|
%
|
% The format of the ScaleImage method is:
|
%
|
% Image *ScaleImage(const Image *image,const size_t columns,
|
% const size_t rows,ExceptionInfo *exception)
|
%
|
% A description of each parameter follows:
|
%
|
% o image: the image.
|
%
|
% o columns: the number of columns in the scaled image.
|
%
|
% o rows: the number of rows in the scaled image.
|
%
|
% o exception: return any errors or warnings in this structure.
|
%
|
*/
|
MagickExport Image *ScaleImage(const Image *image,const size_t columns,
|
const size_t rows,ExceptionInfo *exception)
|
{
|
#define ScaleImageTag "Scale/Image"
|
|
CacheView
|
*image_view,
|
*scale_view;
|
|
double
|
alpha,
|
pixel[CompositePixelChannel],
|
*scale_scanline,
|
*scanline,
|
*x_vector,
|
*y_vector;
|
|
Image
|
*scale_image;
|
|
MagickBooleanType
|
next_column,
|
next_row,
|
proceed,
|
status;
|
|
PixelTrait
|
scale_traits;
|
|
PointInfo
|
scale,
|
span;
|
|
register ssize_t
|
i;
|
|
ssize_t
|
n,
|
number_rows,
|
y;
|
|
/*
|
Initialize scaled image attributes.
|
*/
|
assert(image != (const Image *) NULL);
|
assert(image->signature == MagickCoreSignature);
|
if (image->debug != MagickFalse)
|
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
|
assert(exception != (ExceptionInfo *) NULL);
|
assert(exception->signature == MagickCoreSignature);
|
if ((columns == 0) || (rows == 0))
|
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
|
if ((columns == image->columns) && (rows == image->rows))
|
return(CloneImage(image,0,0,MagickTrue,exception));
|
scale_image=CloneImage(image,columns,rows,MagickTrue,exception);
|
if (scale_image == (Image *) NULL)
|
return((Image *) NULL);
|
if (SetImageStorageClass(scale_image,DirectClass,exception) == MagickFalse)
|
{
|
scale_image=DestroyImage(scale_image);
|
return((Image *) NULL);
|
}
|
/*
|
Allocate memory.
|
*/
|
x_vector=(double *) AcquireQuantumMemory((size_t) image->columns,
|
MaxPixelChannels*sizeof(*x_vector));
|
scanline=x_vector;
|
if (image->rows != scale_image->rows)
|
scanline=(double *) AcquireQuantumMemory((size_t) image->columns,
|
MaxPixelChannels*sizeof(*scanline));
|
scale_scanline=(double *) AcquireQuantumMemory((size_t) scale_image->columns,
|
MaxPixelChannels*sizeof(*scale_scanline));
|
y_vector=(double *) AcquireQuantumMemory((size_t) image->columns,
|
MaxPixelChannels*sizeof(*y_vector));
|
if ((scanline == (double *) NULL) || (scale_scanline == (double *) NULL) ||
|
(x_vector == (double *) NULL) || (y_vector == (double *) NULL))
|
{
|
if ((image->rows != scale_image->rows) && (scanline != (double *) NULL))
|
scanline=(double *) RelinquishMagickMemory(scanline);
|
if (scale_scanline != (double *) NULL)
|
scale_scanline=(double *) RelinquishMagickMemory(scale_scanline);
|
if (x_vector != (double *) NULL)
|
x_vector=(double *) RelinquishMagickMemory(x_vector);
|
if (y_vector != (double *) NULL)
|
y_vector=(double *) RelinquishMagickMemory(y_vector);
|
scale_image=DestroyImage(scale_image);
|
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
|
}
|
/*
|
Scale image.
|
*/
|
number_rows=0;
|
next_row=MagickTrue;
|
span.y=1.0;
|
scale.y=(double) scale_image->rows/(double) image->rows;
|
(void) memset(y_vector,0,(size_t) MaxPixelChannels*image->columns*
|
sizeof(*y_vector));
|
n=0;
|
status=MagickTrue;
|
image_view=AcquireVirtualCacheView(image,exception);
|
scale_view=AcquireAuthenticCacheView(scale_image,exception);
|
for (y=0; y < (ssize_t) scale_image->rows; y++)
|
{
|
register const Quantum
|
*magick_restrict p;
|
|
register Quantum
|
*magick_restrict q;
|
|
register ssize_t
|
x;
|
|
if (status == MagickFalse)
|
break;
|
q=QueueCacheViewAuthenticPixels(scale_view,0,y,scale_image->columns,1,
|
exception);
|
if (q == (Quantum *) NULL)
|
{
|
status=MagickFalse;
|
break;
|
}
|
alpha=1.0;
|
if (scale_image->rows == image->rows)
|
{
|
/*
|
Read a new scanline.
|
*/
|
p=GetCacheViewVirtualPixels(image_view,0,n++,image->columns,1,
|
exception);
|
if (p == (const Quantum *) NULL)
|
{
|
status=MagickFalse;
|
break;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
if (GetPixelWriteMask(image,p) <= (QuantumRange/2))
|
{
|
p+=GetPixelChannels(image);
|
continue;
|
}
|
if (image->alpha_trait != UndefinedPixelTrait)
|
alpha=QuantumScale*GetPixelAlpha(image,p);
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
if ((traits & BlendPixelTrait) == 0)
|
{
|
x_vector[x*GetPixelChannels(image)+i]=(double) p[i];
|
continue;
|
}
|
x_vector[x*GetPixelChannels(image)+i]=alpha*p[i];
|
}
|
p+=GetPixelChannels(image);
|
}
|
}
|
else
|
{
|
/*
|
Scale Y direction.
|
*/
|
while (scale.y < span.y)
|
{
|
if ((next_row != MagickFalse) &&
|
(number_rows < (ssize_t) image->rows))
|
{
|
/*
|
Read a new scanline.
|
*/
|
p=GetCacheViewVirtualPixels(image_view,0,n++,image->columns,1,
|
exception);
|
if (p == (const Quantum *) NULL)
|
{
|
status=MagickFalse;
|
break;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
if (GetPixelWriteMask(image,p) <= (QuantumRange/2))
|
{
|
p+=GetPixelChannels(image);
|
continue;
|
}
|
if (image->alpha_trait != UndefinedPixelTrait)
|
alpha=QuantumScale*GetPixelAlpha(image,p);
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
if ((traits & BlendPixelTrait) == 0)
|
{
|
x_vector[x*GetPixelChannels(image)+i]=(double) p[i];
|
continue;
|
}
|
x_vector[x*GetPixelChannels(image)+i]=alpha*p[i];
|
}
|
p+=GetPixelChannels(image);
|
}
|
number_rows++;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
y_vector[x*GetPixelChannels(image)+i]+=scale.y*
|
x_vector[x*GetPixelChannels(image)+i];
|
span.y-=scale.y;
|
scale.y=(double) scale_image->rows/(double) image->rows;
|
next_row=MagickTrue;
|
}
|
if ((next_row != MagickFalse) && (number_rows < (ssize_t) image->rows))
|
{
|
/*
|
Read a new scanline.
|
*/
|
p=GetCacheViewVirtualPixels(image_view,0,n++,image->columns,1,
|
exception);
|
if (p == (const Quantum *) NULL)
|
{
|
status=MagickFalse;
|
break;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
if (GetPixelWriteMask(image,p) <= (QuantumRange/2))
|
{
|
p+=GetPixelChannels(image);
|
continue;
|
}
|
if (image->alpha_trait != UndefinedPixelTrait)
|
alpha=QuantumScale*GetPixelAlpha(image,p);
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
if ((traits & BlendPixelTrait) == 0)
|
{
|
x_vector[x*GetPixelChannels(image)+i]=(double) p[i];
|
continue;
|
}
|
x_vector[x*GetPixelChannels(image)+i]=alpha*p[i];
|
}
|
p+=GetPixelChannels(image);
|
}
|
number_rows++;
|
next_row=MagickFalse;
|
}
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
pixel[i]=y_vector[x*GetPixelChannels(image)+i]+span.y*
|
x_vector[x*GetPixelChannels(image)+i];
|
scanline[x*GetPixelChannels(image)+i]=pixel[i];
|
y_vector[x*GetPixelChannels(image)+i]=0.0;
|
}
|
}
|
scale.y-=span.y;
|
if (scale.y <= 0)
|
{
|
scale.y=(double) scale_image->rows/(double) image->rows;
|
next_row=MagickTrue;
|
}
|
span.y=1.0;
|
}
|
if (scale_image->columns == image->columns)
|
{
|
/*
|
Transfer scanline to scaled image.
|
*/
|
for (x=0; x < (ssize_t) scale_image->columns; x++)
|
{
|
if (GetPixelWriteMask(scale_image,q) <= (QuantumRange/2))
|
{
|
q+=GetPixelChannels(scale_image);
|
continue;
|
}
|
if (image->alpha_trait != UndefinedPixelTrait)
|
{
|
alpha=QuantumScale*scanline[x*GetPixelChannels(image)+
|
GetPixelChannelOffset(image,AlphaPixelChannel)];
|
alpha=PerceptibleReciprocal(alpha);
|
}
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
scale_traits=GetPixelChannelTraits(scale_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(scale_traits == UndefinedPixelTrait))
|
continue;
|
if ((traits & BlendPixelTrait) == 0)
|
{
|
SetPixelChannel(scale_image,channel,ClampToQuantum(
|
scanline[x*GetPixelChannels(image)+i]),q);
|
continue;
|
}
|
SetPixelChannel(scale_image,channel,ClampToQuantum(alpha*scanline[
|
x*GetPixelChannels(image)+i]),q);
|
}
|
q+=GetPixelChannels(scale_image);
|
}
|
}
|
else
|
{
|
ssize_t
|
t;
|
|
/*
|
Scale X direction.
|
*/
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
pixel[i]=0.0;
|
next_column=MagickFalse;
|
span.x=1.0;
|
t=0;
|
for (x=0; x < (ssize_t) image->columns; x++)
|
{
|
scale.x=(double) scale_image->columns/(double) image->columns;
|
while (scale.x >= span.x)
|
{
|
if (next_column != MagickFalse)
|
{
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
pixel[i]=0.0;
|
t++;
|
}
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
if (traits == UndefinedPixelTrait)
|
continue;
|
pixel[i]+=span.x*scanline[x*GetPixelChannels(image)+i];
|
scale_scanline[t*GetPixelChannels(image)+i]=pixel[i];
|
}
|
scale.x-=span.x;
|
span.x=1.0;
|
next_column=MagickTrue;
|
}
|
if (scale.x > 0)
|
{
|
if (next_column != MagickFalse)
|
{
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
pixel[i]=0.0;
|
next_column=MagickFalse;
|
t++;
|
}
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
pixel[i]+=scale.x*scanline[x*GetPixelChannels(image)+i];
|
span.x-=scale.x;
|
}
|
}
|
if (span.x > 0)
|
{
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
pixel[i]+=span.x*scanline[(x-1)*GetPixelChannels(image)+i];
|
}
|
if ((next_column == MagickFalse) &&
|
(t < (ssize_t) scale_image->columns))
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
scale_scanline[t*GetPixelChannels(image)+i]=pixel[i];
|
/*
|
Transfer scanline to scaled image.
|
*/
|
for (x=0; x < (ssize_t) scale_image->columns; x++)
|
{
|
if (GetPixelWriteMask(scale_image,q) <= (QuantumRange/2))
|
{
|
q+=GetPixelChannels(scale_image);
|
continue;
|
}
|
if (image->alpha_trait != UndefinedPixelTrait)
|
{
|
alpha=QuantumScale*scale_scanline[x*GetPixelChannels(image)+
|
GetPixelChannelOffset(image,AlphaPixelChannel)];
|
alpha=PerceptibleReciprocal(alpha);
|
}
|
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
|
{
|
PixelChannel channel = GetPixelChannelChannel(image,i);
|
PixelTrait traits = GetPixelChannelTraits(image,channel);
|
scale_traits=GetPixelChannelTraits(scale_image,channel);
|
if ((traits == UndefinedPixelTrait) ||
|
(scale_traits == UndefinedPixelTrait))
|
continue;
|
if ((traits & BlendPixelTrait) == 0)
|
{
|
SetPixelChannel(scale_image,channel,ClampToQuantum(
|
scale_scanline[x*GetPixelChannels(image)+i]),q);
|
continue;
|
}
|
SetPixelChannel(scale_image,channel,ClampToQuantum(alpha*
|
scale_scanline[x*GetPixelChannels(image)+i]),q);
|
}
|
q+=GetPixelChannels(scale_image);
|
}
|
}
|
if (SyncCacheViewAuthenticPixels(scale_view,exception) == MagickFalse)
|
{
|
status=MagickFalse;
|
break;
|
}
|
proceed=SetImageProgress(image,ScaleImageTag,(MagickOffsetType) y,
|
image->rows);
|
if (proceed == MagickFalse)
|
{
|
status=MagickFalse;
|
break;
|
}
|
}
|
scale_view=DestroyCacheView(scale_view);
|
image_view=DestroyCacheView(image_view);
|
/*
|
Free allocated memory.
|
*/
|
y_vector=(double *) RelinquishMagickMemory(y_vector);
|
scale_scanline=(double *) RelinquishMagickMemory(scale_scanline);
|
if (scale_image->rows != image->rows)
|
scanline=(double *) RelinquishMagickMemory(scanline);
|
x_vector=(double *) RelinquishMagickMemory(x_vector);
|
scale_image->type=image->type;
|
if (status == MagickFalse)
|
scale_image=DestroyImage(scale_image);
|
return(scale_image);
|
}
|
|
/*
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
% %
|
% %
|
% %
|
% T h u m b n a i l I m a g e %
|
% %
|
% %
|
% %
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
%
|
% ThumbnailImage() changes the size of an image to the given dimensions and
|
% removes any associated profiles. The goal is to produce small low cost
|
% thumbnail images suited for display on the Web.
|
%
|
% The format of the ThumbnailImage method is:
|
%
|
% Image *ThumbnailImage(const Image *image,const size_t columns,
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% const size_t rows,ExceptionInfo *exception)
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%
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% A description of each parameter follows:
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%
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% o image: the image.
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%
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% o columns: the number of columns in the scaled image.
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%
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% o rows: the number of rows in the scaled image.
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%
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% o exception: return any errors or warnings in this structure.
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%
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*/
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MagickExport Image *ThumbnailImage(const Image *image,const size_t columns,
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const size_t rows,ExceptionInfo *exception)
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{
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#define SampleFactor 5
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char
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filename[MagickPathExtent],
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value[MagickPathExtent];
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const char
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*name;
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Image
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*thumbnail_image;
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double
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x_factor,
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y_factor;
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struct stat
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attributes;
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assert(image != (Image *) NULL);
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assert(image->signature == MagickCoreSignature);
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if (image->debug != MagickFalse)
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(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
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assert(exception != (ExceptionInfo *) NULL);
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assert(exception->signature == MagickCoreSignature);
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x_factor=(double) columns/(double) image->columns;
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y_factor=(double) rows/(double) image->rows;
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if ((x_factor*y_factor) > 0.1)
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thumbnail_image=ResizeImage(image,columns,rows,image->filter,exception);
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else
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if (((SampleFactor*columns) < 128) || ((SampleFactor*rows) < 128))
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thumbnail_image=ResizeImage(image,columns,rows,image->filter,exception);
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else
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{
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Image
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*sample_image;
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sample_image=SampleImage(image,SampleFactor*columns,SampleFactor*rows,
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exception);
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if (sample_image == (Image *) NULL)
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return((Image *) NULL);
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thumbnail_image=ResizeImage(sample_image,columns,rows,image->filter,
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exception);
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sample_image=DestroyImage(sample_image);
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}
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if (thumbnail_image == (Image *) NULL)
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return(thumbnail_image);
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(void) ParseAbsoluteGeometry("0x0+0+0",&thumbnail_image->page);
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if (thumbnail_image->alpha_trait == UndefinedPixelTrait)
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(void) SetImageAlphaChannel(thumbnail_image,OpaqueAlphaChannel,exception);
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thumbnail_image->depth=8;
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thumbnail_image->interlace=NoInterlace;
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/*
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Strip all profiles except color profiles.
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*/
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ResetImageProfileIterator(thumbnail_image);
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for (name=GetNextImageProfile(thumbnail_image); name != (const char *) NULL; )
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{
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if ((LocaleCompare(name,"icc") != 0) && (LocaleCompare(name,"icm") != 0))
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{
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(void) DeleteImageProfile(thumbnail_image,name);
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ResetImageProfileIterator(thumbnail_image);
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}
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name=GetNextImageProfile(thumbnail_image);
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}
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(void) DeleteImageProperty(thumbnail_image,"comment");
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(void) CopyMagickString(value,image->magick_filename,MagickPathExtent);
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if (strstr(image->magick_filename,"//") == (char *) NULL)
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(void) FormatLocaleString(value,MagickPathExtent,"file://%s",
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image->magick_filename);
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(void) SetImageProperty(thumbnail_image,"Thumb::URI",value,exception);
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GetPathComponent(image->magick_filename,TailPath,filename);
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(void) CopyMagickString(value,filename,MagickPathExtent);
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if ( GetPathAttributes(image->filename,&attributes) != MagickFalse )
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{
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(void) FormatLocaleString(value,MagickPathExtent,"%.20g",(double)
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attributes.st_mtime);
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(void) SetImageProperty(thumbnail_image,"Thumb::MTime",value,exception);
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}
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(void) FormatLocaleString(value,MagickPathExtent,"%.20g",(double)
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attributes.st_mtime);
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(void) FormatMagickSize(GetBlobSize(image),MagickFalse,"B",MagickPathExtent,
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value);
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(void) SetImageProperty(thumbnail_image,"Thumb::Size",value,exception);
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(void) FormatLocaleString(value,MagickPathExtent,"image/%s",image->magick);
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LocaleLower(value);
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(void) SetImageProperty(thumbnail_image,"Thumb::Mimetype",value,exception);
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(void) SetImageProperty(thumbnail_image,"software",MagickAuthoritativeURL,
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exception);
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(void) FormatLocaleString(value,MagickPathExtent,"%.20g",(double)
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image->magick_columns);
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(void) SetImageProperty(thumbnail_image,"Thumb::Image::Width",value,
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exception);
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(void) FormatLocaleString(value,MagickPathExtent,"%.20g",(double)
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image->magick_rows);
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(void) SetImageProperty(thumbnail_image,"Thumb::Image::Height",value,
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exception);
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(void) FormatLocaleString(value,MagickPathExtent,"%.20g",(double)
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GetImageListLength(image));
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(void) SetImageProperty(thumbnail_image,"Thumb::Document::Pages",value,
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exception);
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return(thumbnail_image);
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}
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