averello/ImageMagick-mirror
1
0
Fork 0
mirror of https://github.com/ImageMagick/ImageMagick.git synced 2026-05-25 11:24:54 +02:00
Code Issues Packages Projects Releases Wiki Activity
Files
main
ImageMagick-mirror/MagickCore/statistic.c
T

3151 lines
95 KiB
C
Raw Permalink Blame History

/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% SSSSS TTTTT AAA TTTTT IIIII SSSSS TTTTT IIIII CCCC %
% SS T A A T I SS T I C %
% SSS T AAAAA T I SSS T I C %
% SS T A A T I SS T I C %
% SSSSS T A A T IIIII SSSSS T IIIII CCCC %
% %
% %
% MagickCore Image Statistical Methods %
% %
% Software Design %
% Cristy %
% July 1992 %
% %
% %
% Copyright @ 1999 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% https://imagemagick.org/license/ %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "MagickCore/studio.h"
#include "MagickCore/accelerate-private.h"
#include "MagickCore/animate.h"
#include "MagickCore/artifact.h"
#include "MagickCore/blob.h"
#include "MagickCore/blob-private.h"
#include "MagickCore/cache.h"
#include "MagickCore/cache-private.h"
#include "MagickCore/cache-view.h"
#include "MagickCore/client.h"
#include "MagickCore/color.h"
#include "MagickCore/color-private.h"
#include "MagickCore/colorspace.h"
#include "MagickCore/colorspace-private.h"
#include "MagickCore/composite.h"
#include "MagickCore/composite-private.h"
#include "MagickCore/compress.h"
#include "MagickCore/constitute.h"
#include "MagickCore/display.h"
#include "MagickCore/draw.h"
#include "MagickCore/enhance.h"
#include "MagickCore/exception.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/gem.h"
#include "MagickCore/gem-private.h"
#include "MagickCore/geometry.h"
#include "MagickCore/list.h"
#include "MagickCore/image-private.h"
#include "MagickCore/magic.h"
#include "MagickCore/magick.h"
#include "MagickCore/memory_.h"
#include "MagickCore/module.h"
#include "MagickCore/monitor.h"
#include "MagickCore/monitor-private.h"
#include "MagickCore/option.h"
#include "MagickCore/paint.h"
#include "MagickCore/pixel-accessor.h"
#include "MagickCore/profile.h"
#include "MagickCore/property.h"
#include "MagickCore/quantize.h"
#include "MagickCore/quantum-private.h"
#include "MagickCore/random_.h"
#include "MagickCore/random-private.h"
#include "MagickCore/resource_.h"
#include "MagickCore/segment.h"
#include "MagickCore/semaphore.h"
#include "MagickCore/signature-private.h"
#include "MagickCore/statistic.h"
#include "MagickCore/statistic-private.h"
#include "MagickCore/string_.h"
#include "MagickCore/thread-private.h"
#include "MagickCore/timer.h"
#include "MagickCore/utility.h"
#include "MagickCore/version.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% E v a l u a t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% EvaluateImage() applies a value to the image with an arithmetic, relational,
% or logical operator to an image. Use these operations to lighten or darken
% an image, to increase or decrease contrast in an image, or to produce the
% "negative" of an image.
%
% The format of the EvaluateImage method is:
%
% MagickBooleanType EvaluateImage(Image *image,
% const MagickEvaluateOperator op,const double value,
% ExceptionInfo *exception)
% MagickBooleanType EvaluateImages(Image *images,
% const MagickEvaluateOperator op,const double value,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o op: A channel op.
%
% o value: A value value.
%
% o exception: return any errors or warnings in this structure.
%
*/
typedef struct _PixelChannels
{
double
channel[MaxPixelChannels];
} PixelChannels;
static PixelChannels **DestroyPixelTLS(const Image *images,
PixelChannels **pixels)
{
ssize_t
i;
size_t
rows;
assert(pixels != (PixelChannels **) NULL);
rows=MagickMax(GetImageListLength(images),(size_t)
GetMagickResourceLimit(ThreadResource));
for (i=0; i < (ssize_t) rows; i++)
if (pixels[i] != (PixelChannels *) NULL)
pixels[i]=(PixelChannels *) RelinquishMagickMemory(pixels[i]);
pixels=(PixelChannels **) RelinquishMagickMemory(pixels);
return(pixels);
}
static PixelChannels **AcquirePixelTLS(const Image *images)
{
const Image
*next;
PixelChannels
**pixels;
ssize_t
i;
size_t
columns,
number_images,
rows;
number_images=GetImageListLength(images);
rows=MagickMax(number_images,(size_t) GetMagickResourceLimit(ThreadResource));
pixels=(PixelChannels **) AcquireQuantumMemory(rows,sizeof(*pixels));
if (pixels == (PixelChannels **) NULL)
return((PixelChannels **) NULL);
(void) memset(pixels,0,rows*sizeof(*pixels));
columns=MagickMax(number_images,MaxPixelChannels);
for (next=images; next != (Image *) NULL; next=next->next)
columns=MagickMax(next->columns,columns);
for (i=0; i < (ssize_t) rows; i++)
{
ssize_t
j;
pixels[i]=(PixelChannels *) AcquireQuantumMemory(columns,sizeof(**pixels));
if (pixels[i] == (PixelChannels *) NULL)
return(DestroyPixelTLS(images,pixels));
for (j=0; j < (ssize_t) columns; j++)
{
ssize_t
k;
for (k=0; k < MaxPixelChannels; k++)
pixels[i][j].channel[k]=0.0;
}
}
return(pixels);
}
static inline double EvaluateMax(const double x,const double y)
{
if (x > y)
return(x);
return(y);
}
#if defined(__cplusplus) || defined(c_plusplus)
extern "C" {
#endif
static int IntensityCompare(const void *x,const void *y)
{
const PixelChannels
*color_1,
*color_2;
double
distance;
ssize_t
i;
color_1=(const PixelChannels *) x;
color_2=(const PixelChannels *) y;
distance=0.0;
for (i=0; i < MaxPixelChannels; i++)
distance+=color_1->channel[i]-(double) color_2->channel[i];
return(distance < 0.0 ? -1 : distance > 0.0 ? 1 : 0);
}
#if defined(__cplusplus) || defined(c_plusplus)
}
#endif
static double ApplyEvaluateOperator(RandomInfo *random_info,const Quantum pixel,
const MagickEvaluateOperator op,const double value)
{
double
result;
ssize_t
i;
result=0.0;
switch (op)
{
case UndefinedEvaluateOperator:
break;
case AbsEvaluateOperator:
{
result=(double) fabs((double) pixel+value);
break;
}
case AddEvaluateOperator:
{
result=(double) pixel+value;
break;
}
case AddModulusEvaluateOperator:
{
/*
This returns a 'floored modulus' of the addition which is a positive
result. It differs from % or fmod() that returns a 'truncated modulus'
result, where floor() is replaced by trunc() and could return a
negative result (which is clipped).
*/
result=(double) pixel+value;
result-=((double) QuantumRange+1.0)*floor(result/((double)
QuantumRange+1.0));
break;
}
case AndEvaluateOperator:
{
result=(double) ((ssize_t) pixel & (ssize_t) (value+0.5));
break;
}
case CosineEvaluateOperator:
{
result=(double) QuantumRange*(0.5*cos((double) (2.0*MagickPI*
QuantumScale*(double) pixel*value))+0.5);
break;
}
case DivideEvaluateOperator:
{
result=(double) pixel/(value == 0.0 ? 1.0 : value);
break;
}
case ExponentialEvaluateOperator:
{
result=(double) QuantumRange*exp(value*QuantumScale*(double) pixel);
break;
}
case GaussianNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,GaussianNoise,
value);
break;
}
case ImpulseNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,ImpulseNoise,
value);
break;
}
case InverseLogEvaluateOperator:
{
result=(double) QuantumRange*pow((value+1.0),QuantumScale*(double)
pixel-1.0)*MagickSafeReciprocal(value);
break;
}
case LaplacianNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,
LaplacianNoise,value);
break;
}
case LeftShiftEvaluateOperator:
{
result=(double) pixel;
for (i=0; i < (ssize_t) value; i++)
result*=2.0;
break;
}
case LogEvaluateOperator:
{
if ((QuantumScale*(double) pixel) >= MagickEpsilon)
result=(double) QuantumRange*log(QuantumScale*value*
(double) pixel+1.0)/log((double) (value+1.0));
break;
}
case MaxEvaluateOperator:
{
result=(double) EvaluateMax((double) pixel,value);
break;
}
case MeanEvaluateOperator:
{
result=(double) pixel+value;
break;
}
case MedianEvaluateOperator:
{
result=(double) pixel+value;
break;
}
case MinEvaluateOperator:
{
result=MagickMin((double) pixel,value);
break;
}
case MultiplicativeNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,
MultiplicativeGaussianNoise,value);
break;
}
case MultiplyEvaluateOperator:
{
result=(double) pixel*value;
break;
}
case OrEvaluateOperator:
{
result=(double) ((ssize_t) pixel | (ssize_t) (value+0.5));
break;
}
case PoissonNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,PoissonNoise,
value);
break;
}
case PowEvaluateOperator:
{
if (fabs(value) <= MagickEpsilon)
break;
if (((double) pixel < 0.0) && ((value-floor(value)) > MagickEpsilon))
result=(double) -((double) QuantumRange*pow(-(QuantumScale*(double)
pixel),value));
else
result=(double) QuantumRange*pow(QuantumScale*(double) pixel,value);
break;
}
case RightShiftEvaluateOperator:
{
result=(double) pixel;
for (i=0; i < (ssize_t) value; i++)
result/=2.0;
break;
}
case RootMeanSquareEvaluateOperator:
{
result=((double) pixel*(double) pixel+value);
break;
}
case SetEvaluateOperator:
{
result=value;
break;
}
case SineEvaluateOperator:
{
result=(double) QuantumRange*(0.5*sin((double) (2.0*MagickPI*
QuantumScale*(double) pixel*value))+0.5);
break;
}
case SubtractEvaluateOperator:
{
result=(double) pixel-value;
break;
}
case SumEvaluateOperator:
{
result=(double) pixel+value;
break;
}
case ThresholdEvaluateOperator:
{
result=(double) (((double) pixel <= value) ? 0 : QuantumRange);
break;
}
case ThresholdBlackEvaluateOperator:
{
result=(double) (((double) pixel <= value) ? 0 : pixel);
break;
}
case ThresholdWhiteEvaluateOperator:
{
result=(double) (((double) pixel > value) ? QuantumRange : pixel);
break;
}
case UniformNoiseEvaluateOperator:
{
result=(double) GenerateDifferentialNoise(random_info,pixel,UniformNoise,
value);
break;
}
case XorEvaluateOperator:
{
result=(double) ((ssize_t) pixel ^ (ssize_t) (value+0.5));
break;
}
}
return(result);
}
static Image *AcquireImageCanvas(const Image *images,ExceptionInfo *exception)
{
const Image
*p,
*q;
size_t
columns,
rows;
q=images;
columns=images->columns;
rows=images->rows;
for (p=images; p != (Image *) NULL; p=p->next)
{
if (p->number_channels > q->number_channels)
q=p;
if (p->columns > columns)
columns=p->columns;
if (p->rows > rows)
rows=p->rows;
}
return(CloneImage(q,columns,rows,MagickTrue,exception));
}
MagickExport Image *EvaluateImages(const Image *images,
const MagickEvaluateOperator op,ExceptionInfo *exception)
{
#define EvaluateImageTag "Evaluate/Image"
CacheView
*evaluate_view,
**image_view;
const Image
*view;
Image
*image;
MagickBooleanType
status;
MagickOffsetType
progress;
PixelChannels
**magick_restrict evaluate_pixels;
RandomInfo
**magick_restrict random_info;
size_t
number_images;
ssize_t
n,
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
assert(images != (Image *) NULL);
assert(images->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",images->filename);
image=AcquireImageCanvas(images,exception);
if (image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
{
image=DestroyImage(image);
return((Image *) NULL);
}
number_images=GetImageListLength(images);
evaluate_pixels=AcquirePixelTLS(images);
if (evaluate_pixels == (PixelChannels **) NULL)
{
image=DestroyImage(image);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",images->filename);
return((Image *) NULL);
}
image_view=(CacheView **) AcquireQuantumMemory(number_images,
sizeof(*image_view));
if (image_view == (CacheView **) NULL)
{
image=DestroyImage(image);
evaluate_pixels=DestroyPixelTLS(images,evaluate_pixels);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",images->filename);
return(image);
}
view=images;
for (n=0; n < (ssize_t) number_images; n++)
{
image_view[n]=AcquireVirtualCacheView(view,exception);
view=GetNextImageInList(view);
}
/*
Evaluate image pixels.
*/
status=MagickTrue;
progress=0;
random_info=AcquireRandomInfoTLS();
evaluate_view=AcquireAuthenticCacheView(image,exception);
if (op == MedianEvaluateOperator)
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,images,image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
const Quantum
**p;
PixelChannels
*evaluate_pixel;
Quantum
*magick_restrict q;
ssize_t
x;
ssize_t
j;
if (status == MagickFalse)
continue;
p=(const Quantum **) AcquireQuantumMemory(number_images,sizeof(*p));
if (p == (const Quantum **) NULL)
{
status=MagickFalse;
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",
images->filename);
continue;
}
for (j=0; j < (ssize_t) number_images; j++)
{
p[j]=GetCacheViewVirtualPixels(image_view[j],0,y,image->columns,1,
exception);
if (p[j] == (const Quantum *) NULL)
break;
}
q=QueueCacheViewAuthenticPixels(evaluate_view,0,y,image->columns,1,
exception);
if ((j < (ssize_t) number_images) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
evaluate_pixel=evaluate_pixels[id];
for (x=0; x < (ssize_t) image->columns; x++)
{
const Image
*next;
ssize_t
i;
next=images;
for (j=0; j < (ssize_t) number_images; j++)
{
for (i=0; i < MaxPixelChannels; i++)
evaluate_pixel[j].channel[i]=0.0;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(next,channel);
PixelTrait evaluate_traits = GetPixelChannelTraits(image,channel);
if (((traits & UpdatePixelTrait) == 0) ||
((evaluate_traits & UpdatePixelTrait) == 0))
continue;
evaluate_pixel[j].channel[i]=ApplyEvaluateOperator(
random_info[id],GetPixelChannel(next,channel,p[j]),op,
evaluate_pixel[j].channel[i]);
}
p[j]+=(ptrdiff_t) GetPixelChannels(next);
next=GetNextImageInList(next);
}
qsort((void *) evaluate_pixel,number_images,sizeof(*evaluate_pixel),
IntensityCompare);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
q[i]=ClampToQuantum(evaluate_pixel[number_images/2].channel[i]);
}
q+=(ptrdiff_t) GetPixelChannels(image);
}
p=(const Quantum **) RelinquishMagickMemory((void *) p);
if (SyncCacheViewAuthenticPixels(evaluate_view,exception) == MagickFalse)
status=MagickFalse;
if (images->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(images,EvaluateImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
}
else
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,images,image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const Image
*next;
const int
id = GetOpenMPThreadId();
const Quantum
**p;
PixelChannels
*evaluate_pixel;
Quantum
*magick_restrict q;
ssize_t
i,
x;
ssize_t
j;
if (status == MagickFalse)
continue;
p=(const Quantum **) AcquireQuantumMemory(number_images,sizeof(*p));
if (p == (const Quantum **) NULL)
{
status=MagickFalse;
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",
images->filename);
continue;
}
for (j=0; j < (ssize_t) number_images; j++)
{
p[j]=GetCacheViewVirtualPixels(image_view[j],0,y,image->columns,1,
exception);
if (p[j] == (const Quantum *) NULL)
break;
}
q=QueueCacheViewAuthenticPixels(evaluate_view,0,y,image->columns,1,
exception);
if ((j < (ssize_t) number_images) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
evaluate_pixel=evaluate_pixels[id];
for (j=0; j < (ssize_t) image->columns; j++)
for (i=0; i < MaxPixelChannels; i++)
evaluate_pixel[j].channel[i]=0.0;
next=images;
for (j=0; j < (ssize_t) number_images; j++)
{
for (x=0; x < (ssize_t) image->columns; x++)
{
for (i=0; i < (ssize_t) GetPixelChannels(next); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(next,channel);
PixelTrait evaluate_traits = GetPixelChannelTraits(image,channel);
if (((traits & UpdatePixelTrait) == 0) ||
((evaluate_traits & UpdatePixelTrait) == 0))
continue;
evaluate_pixel[x].channel[i]=ApplyEvaluateOperator(
random_info[id],GetPixelChannel(next,channel,p[j]),j == 0 ?
AddEvaluateOperator : op,evaluate_pixel[x].channel[i]);
}
p[j]+=(ptrdiff_t) GetPixelChannels(next);
}
next=GetNextImageInList(next);
}
for (x=0; x < (ssize_t) image->columns; x++)
{
switch (op)
{
case MeanEvaluateOperator:
{
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
evaluate_pixel[x].channel[i]/=(double) number_images;
break;
}
case MultiplyEvaluateOperator:
{
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
for (j=0; j < ((ssize_t) number_images-1); j++)
evaluate_pixel[x].channel[i]*=QuantumScale;
}
break;
}
case RootMeanSquareEvaluateOperator:
{
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
evaluate_pixel[x].channel[i]=sqrt(evaluate_pixel[x].channel[i]/
number_images);
break;
}
default:
break;
}
}
for (x=0; x < (ssize_t) image->columns; x++)
{
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
q[i]=ClampToQuantum(evaluate_pixel[x].channel[i]);
}
q+=(ptrdiff_t) GetPixelChannels(image);
}
p=(const Quantum **) RelinquishMagickMemory((void *) p);
if (SyncCacheViewAuthenticPixels(evaluate_view,exception) == MagickFalse)
status=MagickFalse;
if (images->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(images,EvaluateImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
}
for (n=0; n < (ssize_t) number_images; n++)
image_view[n]=DestroyCacheView(image_view[n]);
image_view=(CacheView **) RelinquishMagickMemory(image_view);
evaluate_view=DestroyCacheView(evaluate_view);
evaluate_pixels=DestroyPixelTLS(images,evaluate_pixels);
random_info=DestroyRandomInfoTLS(random_info);
if (status == MagickFalse)
image=DestroyImage(image);
return(image);
}
MagickExport MagickBooleanType EvaluateImage(Image *image,
const MagickEvaluateOperator op,const double value,ExceptionInfo *exception)
{
CacheView
*image_view;
const char
*artifact;
MagickBooleanType
clamp,
status;
MagickOffsetType
progress;
RandomInfo
**magick_restrict random_info;
ssize_t
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
clamp=MagickFalse;
artifact=GetImageArtifact(image,"evaluate:clamp");
if (artifact != (const char *) NULL)
clamp=IsStringTrue(artifact);
random_info=AcquireRandomInfoTLS();
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,image,image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
double
result;
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
result=ApplyEvaluateOperator(random_info[id],q[i],op,value);
if (op == MeanEvaluateOperator)
result/=2.0;
q[i]=clamp != MagickFalse ? ClampPixel(result) : ClampToQuantum(result);
}
q+=(ptrdiff_t) GetPixelChannels(image);
}
if (SyncCacheViewAuthenticPixels(image_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,EvaluateImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
random_info=DestroyRandomInfoTLS(random_info);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% F u n c t i o n I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FunctionImage() applies a value to the image with an arithmetic, relational,
% or logical operator to an image. Use these operations to lighten or darken
% an image, to increase or decrease contrast in an image, or to produce the
% "negative" of an image.
%
% The format of the FunctionImage method is:
%
% MagickBooleanType FunctionImage(Image *image,
% const MagickFunction function,const ssize_t number_parameters,
% const double *parameters,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o function: A channel function.
%
% o parameters: one or more parameters.
%
% o exception: return any errors or warnings in this structure.
%
*/
static Quantum ApplyFunction(Quantum pixel,const MagickFunction function,
const size_t number_parameters,const double *parameters,
ExceptionInfo *exception)
{
double
result;
ssize_t
i;
(void) exception;
result=0.0;
switch (function)
{
case PolynomialFunction:
{
/*
Polynomial: polynomial constants, highest to lowest order (e.g. c0*x^3+
c1*x^2+c2*x+c3).
*/
result=0.0;
for (i=0; i < (ssize_t) number_parameters; i++)
result=result*QuantumScale*(double) pixel+parameters[i];
result*=(double) QuantumRange;
break;
}
case SinusoidFunction:
{
double
amplitude,
bias,
frequency,
phase;
/*
Sinusoid: frequency, phase, amplitude, bias.
*/
frequency=(number_parameters >= 1) ? parameters[0] : 1.0;
phase=(number_parameters >= 2) ? parameters[1] : 0.0;
amplitude=(number_parameters >= 3) ? parameters[2] : 0.5;
bias=(number_parameters >= 4) ? parameters[3] : 0.5;
result=(double) QuantumRange*(amplitude*sin((double) (2.0*
MagickPI*(frequency*QuantumScale*(double) pixel+phase/360.0)))+bias);
break;
}
case ArcsinFunction:
{
double
bias,
center,
range,
width;
/*
Arcsin (pegged at range limits for invalid results): width, center,
range, and bias.
*/
width=(number_parameters >= 1) ? parameters[0] : 1.0;
center=(number_parameters >= 2) ? parameters[1] : 0.5;
range=(number_parameters >= 3) ? parameters[2] : 1.0;
bias=(number_parameters >= 4) ? parameters[3] : 0.5;
result=2.0*MagickSafeReciprocal(width)*(QuantumScale*(double) pixel-
center);
if (result <= -1.0)
result=bias-range/2.0;
else
if (result >= 1.0)
result=bias+range/2.0;
else
result=(double) (range/MagickPI*asin((double) result)+bias);
result*=(double) QuantumRange;
break;
}
case ArctanFunction:
{
double
center,
bias,
range,
slope;
/*
Arctan: slope, center, range, and bias.
*/
slope=(number_parameters >= 1) ? parameters[0] : 1.0;
center=(number_parameters >= 2) ? parameters[1] : 0.5;
range=(number_parameters >= 3) ? parameters[2] : 1.0;
bias=(number_parameters >= 4) ? parameters[3] : 0.5;
result=MagickPI*slope*(QuantumScale*(double) pixel-center);
result=(double) QuantumRange*(range/MagickPI*atan((double) result)+bias);
break;
}
case UndefinedFunction:
break;
}
return(ClampToQuantum(result));
}
MagickExport MagickBooleanType FunctionImage(Image *image,
const MagickFunction function,const size_t number_parameters,
const double *parameters,ExceptionInfo *exception)
{
#define FunctionImageTag "Function/Image "
CacheView
*image_view;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
#if defined(MAGICKCORE_OPENCL_SUPPORT)
if (AccelerateFunctionImage(image,function,number_parameters,parameters,
exception) != MagickFalse)
return(MagickTrue);
#endif
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
q[i]=ApplyFunction(q[i],function,number_parameters,parameters,
exception);
}
q+=(ptrdiff_t) GetPixelChannels(image);
}
if (SyncCacheViewAuthenticPixels(image_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,FunctionImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e E n t r o p y %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageEntropy() returns the entropy of one or more image channels.
%
% The format of the GetImageEntropy method is:
%
% MagickBooleanType GetImageEntropy(const Image *image,double *entropy,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o entropy: the average entropy of the selected channels.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageEntropy(const Image *image,
double *entropy,ExceptionInfo *exception)
{
ChannelStatistics
*channel_statistics;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
channel_statistics=GetImageStatistics(image,exception);
if (channel_statistics == (ChannelStatistics *) NULL)
{
*entropy=NAN;
return(MagickFalse);
}
*entropy=channel_statistics[CompositePixelChannel].entropy;
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e E x t r e m a %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageExtrema() returns the extrema of one or more image channels.
%
% The format of the GetImageExtrema method is:
%
% MagickBooleanType GetImageExtrema(const Image *image,size_t *minima,
% size_t *maxima,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o minima: the minimum value in the channel.
%
% o maxima: the maximum value in the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageExtrema(const Image *image,
size_t *minima,size_t *maxima,ExceptionInfo *exception)
{
double
max,
min;
MagickBooleanType
status;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
status=GetImageRange(image,&min,&max,exception);
*minima=(size_t) ceil(min-0.5);
*maxima=(size_t) floor(max+0.5);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e K u r t o s i s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageKurtosis() returns the kurtosis and skewness of one or more image
% channels.
%
% The format of the GetImageKurtosis method is:
%
% MagickBooleanType GetImageKurtosis(const Image *image,double *kurtosis,
% double *skewness,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o kurtosis: the kurtosis of the channel.
%
% o skewness: the skewness of the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageKurtosis(const Image *image,
double *kurtosis,double *skewness,ExceptionInfo *exception)
{
ChannelStatistics
*channel_statistics;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
channel_statistics=GetImageStatistics(image,exception);
if (channel_statistics == (ChannelStatistics *) NULL)
{
*kurtosis=NAN;
*skewness=NAN;
return(MagickFalse);
}
*kurtosis=channel_statistics[CompositePixelChannel].kurtosis;
*skewness=channel_statistics[CompositePixelChannel].skewness;
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e M e a n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageMean() returns the mean and standard deviation of one or more image
% channels.
%
% The format of the GetImageMean method is:
%
% MagickBooleanType GetImageMean(const Image *image,double *mean,
% double *standard_deviation,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o mean: the average value in the channel.
%
% o standard_deviation: the standard deviation of the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageMean(const Image *image,double *mean,
double *standard_deviation,ExceptionInfo *exception)
{
ChannelStatistics
*channel_statistics;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
channel_statistics=GetImageStatistics(image,exception);
if (channel_statistics == (ChannelStatistics *) NULL)
{
*mean=NAN;
*standard_deviation=NAN;
return(MagickFalse);
}
*mean=channel_statistics[CompositePixelChannel].mean;
*standard_deviation=
channel_statistics[CompositePixelChannel].standard_deviation;
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e M e d i a n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageMedian() returns the median pixel of one or more image channels.
%
% The format of the GetImageMedian method is:
%
% MagickBooleanType GetImageMedian(const Image *image,double *median,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o median: the average value in the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageMedian(const Image *image,double *median,
ExceptionInfo *exception)
{
ChannelStatistics
*channel_statistics;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
channel_statistics=GetImageStatistics(image,exception);
if (channel_statistics == (ChannelStatistics *) NULL)
{
*median=NAN;
return(MagickFalse);
}
*median=channel_statistics[CompositePixelChannel].median;
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e M o m e n t s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageMoments() returns the normalized moments of one or more image
% channels.
%
% The format of the GetImageMoments method is:
%
% ChannelMoments *GetImageMoments(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 ChannelMoments *GetImageMoments(const Image *image,
ExceptionInfo *exception)
{
#define MaxNumberImageMoments 8
CacheView
*image_view;
ChannelMoments
*channel_moments;
double
channels,
M00[2*MaxPixelChannels+1] = { 0.0 },
M01[2*MaxPixelChannels+1] = { 0.0 },
M02[2*MaxPixelChannels+1] = { 0.0 },
M03[2*MaxPixelChannels+1] = { 0.0 },
M10[2*MaxPixelChannels+1] = { 0.0 },
M11[2*MaxPixelChannels+1] = { 0.0 },
M12[2*MaxPixelChannels+1] = { 0.0 },
M20[2*MaxPixelChannels+1] = { 0.0 },
M21[2*MaxPixelChannels+1] = { 0.0 },
M22[2*MaxPixelChannels+1] = { 0.0 },
M30[2*MaxPixelChannels+1] = { 0.0 };
PointInfo
centroid[2*MaxPixelChannels+1] = {{ 0 }};
ssize_t
c,
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
channel_moments=(ChannelMoments *) AcquireQuantumMemory(MaxPixelChannels+1,
sizeof(*channel_moments));
if (channel_moments == (ChannelMoments *) NULL)
return(channel_moments);
(void) memset(channel_moments,0,(MaxPixelChannels+1)*
sizeof(*channel_moments));
image_view=AcquireVirtualCacheView(image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
/*
Compute center of mass (centroid).
*/
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
double
pixel;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
pixel=QuantumScale*p[i];
M00[channel]+=pixel;
M00[CompositePixelChannel]+=pixel;
M10[channel]+=x*pixel;
M10[CompositePixelChannel]+=x*pixel;
M01[channel]+=y*pixel;
M01[CompositePixelChannel]+=y*pixel;
}
p+=(ptrdiff_t) GetPixelChannels(image);
}
}
for (c=0; c <= MaxPixelChannels; c++)
{
/*
Compute center of mass (centroid).
*/
centroid[c].x=M10[c]*MagickSafeReciprocal(M00[c]);
centroid[c].y=M01[c]*MagickSafeReciprocal(M00[c]);
}
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
/*
Compute the image moments.
*/
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
M11[channel]+=(x-centroid[channel].x)*(y-centroid[channel].y)*
QuantumScale*(double) p[i];
M11[CompositePixelChannel]+=(x-centroid[channel].x)*(y-
centroid[channel].y)*QuantumScale*(double) p[i];
M20[channel]+=(x-centroid[channel].x)*(x-centroid[channel].x)*
QuantumScale*(double) p[i];
M20[CompositePixelChannel]+=(x-centroid[channel].x)*(x-
centroid[channel].x)*QuantumScale*(double) p[i];
M02[channel]+=(y-centroid[channel].y)*(y-centroid[channel].y)*
QuantumScale*(double) p[i];
M02[CompositePixelChannel]+=(y-centroid[channel].y)*(y-
centroid[channel].y)*QuantumScale*(double) p[i];
M21[channel]+=(x-centroid[channel].x)*(x-centroid[channel].x)*
(y-centroid[channel].y)*QuantumScale*(double) p[i];
M21[CompositePixelChannel]+=(x-centroid[channel].x)*(x-
centroid[channel].x)*(y-centroid[channel].y)*QuantumScale*(double)
p[i];
M12[channel]+=(x-centroid[channel].x)*(y-centroid[channel].y)*
(y-centroid[channel].y)*QuantumScale*(double) p[i];
M12[CompositePixelChannel]+=(x-centroid[channel].x)*(y-
centroid[channel].y)*(y-centroid[channel].y)*QuantumScale*(double)
p[i];
M22[channel]+=(x-centroid[channel].x)*(x-centroid[channel].x)*
(y-centroid[channel].y)*(y-centroid[channel].y)*QuantumScale*(double)
p[i];
M22[CompositePixelChannel]+=(x-centroid[channel].x)*(x-
centroid[channel].x)*(y-centroid[channel].y)*(y-centroid[channel].y)*
QuantumScale*(double) p[i];
M30[channel]+=(x-centroid[channel].x)*(x-centroid[channel].x)*
(x-centroid[channel].x)*QuantumScale*(double) p[i];
M30[CompositePixelChannel]+=(x-centroid[channel].x)*(x-
centroid[channel].x)*(x-centroid[channel].x)*QuantumScale*(double)
p[i];
M03[channel]+=(y-centroid[channel].y)*(y-centroid[channel].y)*
(y-centroid[channel].y)*QuantumScale*(double) p[i];
M03[CompositePixelChannel]+=(y-centroid[channel].y)*(y-
centroid[channel].y)*(y-centroid[channel].y)*QuantumScale*(double)
p[i];
}
p+=(ptrdiff_t) GetPixelChannels(image);
}
}
channels=(double) GetImageChannels(image);
M00[CompositePixelChannel]/=channels;
M01[CompositePixelChannel]/=channels;
M02[CompositePixelChannel]/=channels;
M03[CompositePixelChannel]/=channels;
M10[CompositePixelChannel]/=channels;
M11[CompositePixelChannel]/=channels;
M12[CompositePixelChannel]/=channels;
M20[CompositePixelChannel]/=channels;
M21[CompositePixelChannel]/=channels;
M22[CompositePixelChannel]/=channels;
M30[CompositePixelChannel]/=channels;
for (c=0; c <= MaxPixelChannels; c++)
{
/*
Compute elliptical angle, major and minor axes, eccentricity, & intensity.
*/
channel_moments[c].centroid=centroid[c];
channel_moments[c].ellipse_axis.x=sqrt((2.0*MagickSafeReciprocal(M00[c]))*
((M20[c]+M02[c])+sqrt(4.0*M11[c]*M11[c]+(M20[c]-M02[c])*
(M20[c]-M02[c]))));
channel_moments[c].ellipse_axis.y=sqrt((2.0*MagickSafeReciprocal(M00[c]))*
((M20[c]+M02[c])-sqrt(4.0*M11[c]*M11[c]+(M20[c]-M02[c])*
(M20[c]-M02[c]))));
channel_moments[c].ellipse_angle=RadiansToDegrees(1.0/2.0*atan(2.0*
M11[c]*MagickSafeReciprocal(M20[c]-M02[c])));
if (fabs(M11[c]) < 0.0)
{
if ((fabs(M20[c]-M02[c]) >= 0.0) && ((M20[c]-M02[c]) < 0.0))
channel_moments[c].ellipse_angle+=90.0;
}
else
if (M11[c] < 0.0)
{
if (fabs(M20[c]-M02[c]) >= 0.0)
{
if ((M20[c]-M02[c]) < 0.0)
channel_moments[c].ellipse_angle+=90.0;
else
channel_moments[c].ellipse_angle+=180.0;
}
}
else
if ((fabs(M20[c]-M02[c]) >= 0.0) && ((M20[c]-M02[c]) < 0.0))
channel_moments[c].ellipse_angle+=90.0;
channel_moments[c].ellipse_eccentricity=sqrt(1.0-(
channel_moments[c].ellipse_axis.y*
channel_moments[c].ellipse_axis.y*MagickSafeReciprocal(
channel_moments[c].ellipse_axis.x*
channel_moments[c].ellipse_axis.x)));
channel_moments[c].ellipse_intensity=M00[c]*
MagickSafeReciprocal(MagickPI*channel_moments[c].ellipse_axis.x*
channel_moments[c].ellipse_axis.y+MagickEpsilon);
}
for (c=0; c <= MaxPixelChannels; c++)
{
/*
Normalize image moments.
*/
M10[c]=0.0;
M01[c]=0.0;
M11[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(1.0+1.0)/2.0));
M20[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(2.0+0.0)/2.0));
M02[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(0.0+2.0)/2.0));
M21[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(2.0+1.0)/2.0));
M12[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(1.0+2.0)/2.0));
M22[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(2.0+2.0)/2.0));
M30[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(3.0+0.0)/2.0));
M03[c]*=MagickSafeReciprocal(pow(M00[c],1.0+(0.0+3.0)/2.0));
M00[c]=1.0;
}
image_view=DestroyCacheView(image_view);
for (c=0; c <= MaxPixelChannels; c++)
{
/*
Compute Hu invariant moments.
*/
channel_moments[c].invariant[0]=M20[c]+M02[c];
channel_moments[c].invariant[1]=(M20[c]-M02[c])*(M20[c]-M02[c])+4.0*M11[c]*
M11[c];
channel_moments[c].invariant[2]=(M30[c]-3.0*M12[c])*(M30[c]-3.0*M12[c])+
(3.0*M21[c]-M03[c])*(3.0*M21[c]-M03[c]);
channel_moments[c].invariant[3]=(M30[c]+M12[c])*(M30[c]+M12[c])+(M21[c]+
M03[c])*(M21[c]+M03[c]);
channel_moments[c].invariant[4]=(M30[c]-3.0*M12[c])*(M30[c]+M12[c])*
((M30[c]+M12[c])*(M30[c]+M12[c])-3.0*(M21[c]+M03[c])*(M21[c]+M03[c]))+
(3.0*M21[c]-M03[c])*(M21[c]+M03[c])*(3.0*(M30[c]+M12[c])*(M30[c]+M12[c])-
(M21[c]+M03[c])*(M21[c]+M03[c]));
channel_moments[c].invariant[5]=(M20[c]-M02[c])*((M30[c]+M12[c])*(M30[c]+
M12[c])-(M21[c]+M03[c])*(M21[c]+M03[c]))+4.0*M11[c]*(M30[c]+M12[c])*
(M21[c]+M03[c]);
channel_moments[c].invariant[6]=(3.0*M21[c]-M03[c])*(M30[c]+M12[c])*
((M30[c]+M12[c])*(M30[c]+M12[c])-3.0*(M21[c]+M03[c])*(M21[c]+M03[c]))-
(M30[c]-3*M12[c])*(M21[c]+M03[c])*(3.0*(M30[c]+M12[c])*(M30[c]+M12[c])-
(M21[c]+M03[c])*(M21[c]+M03[c]));
channel_moments[c].invariant[7]=M11[c]*((M30[c]+M12[c])*(M30[c]+M12[c])-
(M03[c]+M21[c])*(M03[c]+M21[c]))-(M20[c]-M02[c])*(M30[c]+M12[c])*
(M03[c]+M21[c]);
}
if (y < (ssize_t) image->rows)
channel_moments=(ChannelMoments *) RelinquishMagickMemory(channel_moments);
return(channel_moments);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l P e r c e p t u a l H a s h %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImagePerceptualHash() returns the perceptual hash of one or more
% image channels.
%
% The format of the GetImagePerceptualHash method is:
%
% ChannelPerceptualHash *GetImagePerceptualHash(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 ChannelPerceptualHash *GetImagePerceptualHash(const Image *image,
ExceptionInfo *exception)
{
ChannelPerceptualHash
*perceptual_hash;
char
*colorspaces,
*p,
*q;
const char
*artifact;
MagickBooleanType
status;
ssize_t
i;
perceptual_hash=(ChannelPerceptualHash *) AcquireQuantumMemory(
MaxPixelChannels+1UL,sizeof(*perceptual_hash));
if (perceptual_hash == (ChannelPerceptualHash *) NULL)
return((ChannelPerceptualHash *) NULL);
artifact=GetImageArtifact(image,"phash:colorspaces");
if (artifact != (const char *) NULL)
colorspaces=AcquireString(artifact);
else
colorspaces=AcquireString("xyY,HSB");
perceptual_hash[0].number_colorspaces=0;
perceptual_hash[0].number_channels=0;
q=colorspaces;
for (i=0; (p=StringToken(",",&q)) != (char *) NULL; i++)
{
ChannelMoments
*moments;
Image
*hash_image;
size_t
j;
ssize_t
channel,
colorspace;
if (i >= MaximumNumberOfPerceptualColorspaces)
break;
colorspace=ParseCommandOption(MagickColorspaceOptions,MagickFalse,p);
if (colorspace < 0)
break;
perceptual_hash[0].colorspace[i]=(ColorspaceType) colorspace;
hash_image=BlurImage(image,0.0,1.0,exception);
if (hash_image == (Image *) NULL)
break;
hash_image->depth=8;
status=TransformImageColorspace(hash_image,(ColorspaceType) colorspace,
exception);
if (status == MagickFalse)
break;
moments=GetImageMoments(hash_image,exception);
perceptual_hash[0].number_colorspaces++;
perceptual_hash[0].number_channels+=GetImageChannels(hash_image);
hash_image=DestroyImage(hash_image);
if (moments == (ChannelMoments *) NULL)
break;
for (channel=0; channel <= MaxPixelChannels; channel++)
for (j=0; j < MaximumNumberOfImageMoments; j++)
perceptual_hash[channel].phash[i][j]=
(-MagickSafeLog10(moments[channel].invariant[j]));
moments=(ChannelMoments *) RelinquishMagickMemory(moments);
}
colorspaces=DestroyString(colorspaces);
return(perceptual_hash);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e R a n g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageRange() returns the range of one or more image channels.
%
% The format of the GetImageRange method is:
%
% MagickBooleanType GetImageRange(const Image *image,double *minima,
% double *maxima,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o minima: the minimum value in the channel.
%
% o maxima: the maximum value in the channel.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageRange(const Image *image,double *minima,
double *maxima,ExceptionInfo *exception)
{
typedef struct
{
double
maxima,
minima;
} RangeInfo;
CacheView
*image_view;
MagickBooleanType
status;
RangeInfo
range_info = { -MagickMaximumValue, MagickMaximumValue };
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(range_info,status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
RangeInfo
channel_range;
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;
}
channel_range=range_info;
for (x=0; x < (ssize_t) image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
if ((double) p[i] > channel_range.maxima)
channel_range.maxima=(double) p[i];
if ((double) p[i] < channel_range.minima)
channel_range.minima=(double) p[i];
}
p+=(ptrdiff_t) GetPixelChannels(image);
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetImageRange)
#endif
{
if (channel_range.maxima > range_info.maxima)
range_info.maxima=channel_range.maxima;
if (channel_range.minima < range_info.minima)
range_info.minima=channel_range.minima;
}
}
image_view=DestroyCacheView(image_view);
*maxima=range_info.maxima;
*minima=range_info.minima;
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e S t a t i s t i c s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageStatistics() returns statistics for each channel in the image. The
% statistics include the channel depth, its minima, maxima, mean, standard
% deviation, kurtosis and skewness. You can access the red channel mean, for
% example, like this:
%
% channel_statistics=GetImageStatistics(image,exception);
% red_mean=channel_statistics[RedPixelChannel].mean;
%
% Use MagickRelinquishMemory() to free the statistics buffer.
%
% The format of the GetImageStatistics method is:
%
% ChannelStatistics *GetImageStatistics(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.
%
*/
static ssize_t GetMedianPixel(Quantum *pixels,const size_t n)
{
#define SwapPixels(alpha,beta) \
{ \
Quantum gamma=(alpha); \
(alpha)=(beta);(beta)=gamma; \
}
ssize_t
low = 0,
high = (ssize_t) n-1,
median = (low+high)/2;
for ( ; ; )
{
ssize_t
l = low+1,
h = high,
mid = (low+high)/2;
if (high <= low)
return(median);
if (high == (low+1))
{
if (pixels[low] > pixels[high])
SwapPixels(pixels[low],pixels[high]);
return(median);
}
if (pixels[mid] > pixels[high])
SwapPixels(pixels[mid],pixels[high]);
if (pixels[low] > pixels[high])
SwapPixels(pixels[low], pixels[high]);
if (pixels[mid] > pixels[low])
SwapPixels(pixels[mid],pixels[low]);
SwapPixels(pixels[mid],pixels[low+1]);
for ( ; ; )
{
do l++; while (pixels[low] > pixels[l]);
do h--; while (pixels[h] > pixels[low]);
if (h < l)
break;
SwapPixels(pixels[l],pixels[h]);
}
SwapPixels(pixels[low],pixels[h]);
if (h <= median)
low=l;
if (h >= median)
high=h-1;
}
}
static inline long double MagickSafeReciprocalLD(const long double x)
{
long double
sign;
/*
Return 1/x where x is perceptible (not unlimited or infinitesimal).
*/
sign=x < 0.0 ? -1.0 : 1.0;
if ((sign*x) >= MagickEpsilon)
return(1.0/x);
return(sign/MagickEpsilon);
}
MagickExport ChannelStatistics *GetImageStatistics(const Image *image,
ExceptionInfo *exception)
{
ChannelStatistics
*channel_statistics;
double
channels,
*histogram;
long double
area;
MagickStatusType
status;
MemoryInfo
*median_info;
Quantum
*median;
QuantumAny
range;
size_t
depth;
ssize_t
i,
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
histogram=(double *) AcquireQuantumMemory(MaxMap+1UL,
MagickMax(GetPixelChannels(image),1)*sizeof(*histogram));
channel_statistics=(ChannelStatistics *) AcquireQuantumMemory(
MaxPixelChannels+1,sizeof(*channel_statistics));
if ((channel_statistics == (ChannelStatistics *) NULL) ||
(histogram == (double *) NULL))
{
if (histogram != (double *) NULL)
histogram=(double *) RelinquishMagickMemory(histogram);
if (channel_statistics != (ChannelStatistics *) NULL)
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(channel_statistics);
}
(void) memset(channel_statistics,0,(MaxPixelChannels+1)*
sizeof(*channel_statistics));
for (i=0; i <= (ssize_t) MaxPixelChannels; i++)
{
ChannelStatistics *cs = channel_statistics+i;
cs->area=0.0;
cs->depth=1;
cs->maxima=(-MagickMaximumValue);
cs->minima=MagickMaximumValue;
cs->sum=0.0;
cs->sumLD=0.0;
cs->mean=0.0;
cs->standard_deviation=0.0;
cs->variance=0.0;
cs->skewness=0.0;
cs->kurtosis=0.0;
cs->entropy=0.0;
}
(void) memset(histogram,0,(MaxMap+1)*GetPixelChannels(image)*
sizeof(*histogram));
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
/*
Compute pixel statistics.
*/
p=GetVirtualPixels(image,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (GetPixelReadMask(image,p) <= (QuantumRange/2))
{
p+=(ptrdiff_t) GetPixelChannels(image);
continue;
}
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
ChannelStatistics
*cs;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
cs=channel_statistics+channel;
if (cs->depth != MAGICKCORE_QUANTUM_DEPTH)
{
depth=cs->depth;
range=GetQuantumRange(depth);
status=p[i] != ScaleAnyToQuantum(ScaleQuantumToAny(p[i],range),
range) ? MagickTrue : MagickFalse;
if (status != MagickFalse)
{
cs->depth++;
if (cs->depth > channel_statistics[CompositePixelChannel].depth)
channel_statistics[CompositePixelChannel].depth=cs->depth;
i--;
continue;
}
}
cs->area++;
if ((double) p[i] < cs->minima)
cs->minima=(double) p[i];
if ((double) p[i] > cs->maxima)
cs->maxima=(double) p[i];
histogram[(ssize_t) GetPixelChannels(image)*ScaleQuantumToMap(
ClampToQuantum((double) p[i]))+i]++;
cs->sumLD+=(long double) p[i];
/*
sum_squared, sum_cubed and sum_fourth_power are not used in
MagickCore or MagickWand, but are made available in
Magick++/lib/Statistic.cpp, so we need to calculate these.
*/
cs->sum_squared+=(double) p[i]*(double) p[i];
cs->sum_cubed+=(double) p[i]*(double) p[i]*(double) p[i];
cs->sum_fourth_power+=(double) p[i]*(double) p[i]*(double) p[i]*
(double) p[i];
{
/* Calculate running totals for Welford's method.
*/
double
n = cs->area,
n1 = cs->area-1;
long double
delta,
delta_n,
delta_n2,
term1;
delta=(double) p[i]-cs->M1;
delta_n=delta/n;
delta_n2=delta_n*delta_n;
term1=delta*delta_n*n1;
cs->M4+=term1*delta_n2*(n*n-3.0*n+3.0)+6.0*delta_n2*cs->M2-4.0*
delta_n*cs->M3;
cs->M3+=term1*delta_n*(n-2.0)-3.0*delta_n*cs->M2;
cs->M2+=term1;
cs->M1+=delta_n;
}
}
p+=(ptrdiff_t) GetPixelChannels(image);
}
}
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
ChannelStatistics
*cs;
double
adj_area = 1.0;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
cs=channel_statistics+(ssize_t) channel;
cs->mean=0.0;
if (cs->area > 0)
{
cs->mean=(double) (cs->sumLD/(long double) cs->area);
if (cs->area > 1.0)
adj_area=cs->area/(cs->area-1.0);
}
cs->sum=(double) cs->sum;
if (cs->M2 == 0.0)
{
cs->standard_deviation=0.0;
cs->variance=0.0;
cs->skewness=0.0;
cs->kurtosis=0.0;
}
else
{
if (cs->area > 1.0)
cs->standard_deviation=(double) sqrtl(cs->M2/((long double)
cs->area-1.0));
else
cs->standard_deviation=(double) sqrtl(cs->M2/((long double)
cs->area));
cs->variance=cs->standard_deviation*cs->standard_deviation;
cs->skewness=(double) (sqrtl(cs->area)*cs->M3/powl(cs->M2*adj_area,
1.5));
cs->kurtosis=(double) (cs->area*cs->M4/(cs->M2*cs->M2*adj_area*
adj_area)-3.0);
}
}
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
ChannelStatistics
*cs;
double
number_bins;
ssize_t
j;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
cs=channel_statistics+(ssize_t) channel;
if (cs->area > 0.0)
{
cs->sum/=cs->area;
cs->sum_squared/=cs->area;
cs->sum_cubed/=cs->area;
cs->sum_fourth_power/=cs->area;
}
/*
Compute pixel entropy.
*/
number_bins=0.0;
for (j=0; j <= (ssize_t) MaxMap; j++)
if (histogram[(ssize_t) GetPixelChannels(image)*j+i] > 0.0)
number_bins++;
area=MagickSafeReciprocalLD(channel_statistics[channel].area);
number_bins=(double) MagickSafeReciprocalLD((long double) log2(number_bins));
for (j=0; j <= (ssize_t) MaxMap; j++)
{
double
entropy,
count;
count=(double) (area*histogram[(ssize_t) GetPixelChannels(image)*j+i]);
entropy=-count*log2(count)*number_bins;
if (IsNaN(entropy) != 0)
continue;
channel_statistics[channel].entropy+=(double) entropy;
channel_statistics[CompositePixelChannel].entropy+=((double) entropy/
GetPixelChannels(image));
}
}
histogram=(double *) RelinquishMagickMemory(histogram);
median_info=AcquireVirtualMemory(image->columns,image->rows*sizeof(*median));
if (median_info == (MemoryInfo *) NULL)
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
else
{
median=(Quantum *) GetVirtualMemoryBlob(median_info);
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
size_t
n = 0;
/*
Compute median statistics for each channel.
*/
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
for (y=0; y < (ssize_t) image->rows; y++)
{
const Quantum
*magick_restrict p;
ssize_t
x;
p=GetVirtualPixels(image,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
break;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (GetPixelReadMask(image,p) <= (QuantumRange/2))
{
p+=(ptrdiff_t) GetPixelChannels(image);
continue;
}
median[n++]=p[i];
p+=(ptrdiff_t) GetPixelChannels(image);
}
}
channel_statistics[channel].median=(double) median[
GetMedianPixel(median,n)];
}
median_info=RelinquishVirtualMemory(median_info);
}
{
ChannelStatistics *cs_comp = channel_statistics+CompositePixelChannel;
cs_comp->sum=0.0;
cs_comp->sum_squared=0.0;
cs_comp->sum_cubed=0.0;
cs_comp->sum_fourth_power=0.0;
cs_comp->maxima=(-MagickMaximumValue);
cs_comp->minima=MagickMaximumValue;
cs_comp->area=0.0;
cs_comp->mean=0.0;
cs_comp->median=0.0;
cs_comp->variance=0.0;
cs_comp->standard_deviation=0.0;
cs_comp->entropy=0.0;
cs_comp->skewness=0.0;
cs_comp->kurtosis=0.0;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
ChannelStatistics
*cs;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
cs=channel_statistics+channel;
if (cs_comp->maxima < cs->maxima)
cs_comp->maxima=cs->maxima;
if (cs_comp->minima > cs->minima)
cs_comp->minima=cs->minima;
cs_comp->sum+=cs->sum;
cs_comp->sum_squared+=cs->sum_squared;
cs_comp->sum_cubed+=cs->sum_cubed;
cs_comp->sum_fourth_power+=cs->sum_fourth_power;
cs_comp->median+=cs->median;
cs_comp->area+=cs->area;
cs_comp->mean+=cs->mean;
cs_comp->variance+=cs->variance;
cs_comp->standard_deviation+=cs->standard_deviation;
cs_comp->skewness+=cs->skewness;
cs_comp->kurtosis+=cs->kurtosis;
cs_comp->entropy+=cs->entropy;
}
channels=(double) GetImageChannels(image);
cs_comp->sum/=channels;
cs_comp->sum_squared/=channels;
cs_comp->sum_cubed/=channels;
cs_comp->sum_fourth_power/=channels;
cs_comp->median/=channels;
cs_comp->area/=channels;
cs_comp->mean/=channels;
cs_comp->variance/=channels;
cs_comp->standard_deviation/=channels;
cs_comp->skewness/=channels;
cs_comp->kurtosis/=channels;
cs_comp->entropy/=channels;
}
if (y < (ssize_t) image->rows)
channel_statistics=(ChannelStatistics *) RelinquishMagickMemory(
channel_statistics);
return(channel_statistics);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P o l y n o m i a l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PolynomialImage() returns a new image where each pixel is the sum of the
% pixels in the image sequence after applying its corresponding terms
% (coefficient and degree pairs).
%
% The format of the PolynomialImage method is:
%
% Image *PolynomialImage(const Image *images,const size_t number_terms,
% const double *terms,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o images: the image sequence.
%
% o number_terms: the number of terms in the list. The actual list length
% is 2 x number_terms + 1 (the constant).
%
% o terms: the list of polynomial coefficients and degree pairs and a
% constant.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *PolynomialImage(const Image *images,
const size_t number_terms,const double *terms,ExceptionInfo *exception)
{
#define PolynomialImageTag "Polynomial/Image"
CacheView
*polynomial_view;
Image
*image;
MagickBooleanType
status;
MagickOffsetType
progress;
PixelChannels
**magick_restrict polynomial_pixels;
size_t
number_images;
ssize_t
y;
assert(images != (Image *) NULL);
assert(images->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",images->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
image=AcquireImageCanvas(images,exception);
if (image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
{
image=DestroyImage(image);
return((Image *) NULL);
}
number_images=GetImageListLength(images);
polynomial_pixels=AcquirePixelTLS(images);
if (polynomial_pixels == (PixelChannels **) NULL)
{
image=DestroyImage(image);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",images->filename);
return((Image *) NULL);
}
/*
Polynomial image pixels.
*/
status=MagickTrue;
progress=0;
polynomial_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
CacheView
*image_view;
const Image
*next;
const int
id = GetOpenMPThreadId();
PixelChannels
*polynomial_pixel;
Quantum
*magick_restrict q;
ssize_t
i,
j,
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(polynomial_view,0,y,image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
polynomial_pixel=polynomial_pixels[id];
for (j=0; j < (ssize_t) image->columns; j++)
for (i=0; i < MaxPixelChannels; i++)
polynomial_pixel[j].channel[i]=0.0;
next=images;
for (j=0; j < (ssize_t) number_images; j++)
{
const Quantum
*p;
if (j >= (ssize_t) number_terms)
continue;
image_view=AcquireVirtualCacheView(next,exception);
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const Quantum *) NULL)
{
image_view=DestroyCacheView(image_view);
break;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
for (i=0; i < (ssize_t) GetPixelChannels(next); i++)
{
MagickRealType
coefficient,
degree;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(next,channel);
PixelTrait polynomial_traits = GetPixelChannelTraits(image,channel);
if (((traits & UpdatePixelTrait) == 0) ||
((polynomial_traits & UpdatePixelTrait) == 0))
continue;
coefficient=(MagickRealType) terms[2*j];
degree=(MagickRealType) terms[(j << 1)+1];
polynomial_pixel[x].channel[i]+=coefficient*
pow(QuantumScale*(double) GetPixelChannel(image,channel,p),degree);
}
p+=(ptrdiff_t) GetPixelChannels(next);
}
image_view=DestroyCacheView(image_view);
next=GetNextImageInList(next);
}
for (x=0; x < (ssize_t) image->columns; x++)
{
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
if ((traits & UpdatePixelTrait) == 0)
continue;
q[i]=ClampToQuantum((double) QuantumRange*
polynomial_pixel[x].channel[i]);
}
q+=(ptrdiff_t) GetPixelChannels(image);
}
if (SyncCacheViewAuthenticPixels(polynomial_view,exception) == MagickFalse)
status=MagickFalse;
if (images->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(images,PolynomialImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
polynomial_view=DestroyCacheView(polynomial_view);
polynomial_pixels=DestroyPixelTLS(images,polynomial_pixels);
if (status == MagickFalse)
image=DestroyImage(image);
return(image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S t a t i s t i c I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% StatisticImage() makes each pixel the min / max / median / mode / etc. of
% the neighborhood of the specified width and height.
%
% The format of the StatisticImage method is:
%
% Image *StatisticImage(const Image *image,const StatisticType type,
% const size_t width,const size_t height,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o type: the statistic type (median, mode, etc.).
%
% o width: the width of the pixel neighborhood.
%
% o height: the height of the pixel neighborhood.
%
% o exception: return any errors or warnings in this structure.
%
*/
typedef struct _SkipNode
{
size_t
next[9],
count,
signature;
} SkipNode;
typedef struct _SkipList
{
ssize_t
level;
SkipNode
*nodes;
} SkipList;
typedef struct _PixelList
{
size_t
length,
seed;
SkipList
skip_list;
size_t
signature;
} PixelList;
static PixelList *DestroyPixelList(PixelList *pixel_list)
{
if (pixel_list == (PixelList *) NULL)
return((PixelList *) NULL);
if (pixel_list->skip_list.nodes != (SkipNode *) NULL)
pixel_list->skip_list.nodes=(SkipNode *) RelinquishAlignedMemory(
pixel_list->skip_list.nodes);
pixel_list=(PixelList *) RelinquishMagickMemory(pixel_list);
return(pixel_list);
}
static PixelList **DestroyPixelListTLS(PixelList **pixel_list)
{
ssize_t
i;
assert(pixel_list != (PixelList **) NULL);
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
if (pixel_list[i] != (PixelList *) NULL)
pixel_list[i]=DestroyPixelList(pixel_list[i]);
pixel_list=(PixelList **) RelinquishMagickMemory(pixel_list);
return(pixel_list);
}
static PixelList *AcquirePixelList(const size_t width,const size_t height)
{
PixelList
*pixel_list;
pixel_list=(PixelList *) AcquireMagickMemory(sizeof(*pixel_list));
if (pixel_list == (PixelList *) NULL)
return(pixel_list);
(void) memset((void *) pixel_list,0,sizeof(*pixel_list));
pixel_list->length=width*height;
pixel_list->skip_list.nodes=(SkipNode *) AcquireAlignedMemory(65537UL,
sizeof(*pixel_list->skip_list.nodes));
if (pixel_list->skip_list.nodes == (SkipNode *) NULL)
return(DestroyPixelList(pixel_list));
(void) memset(pixel_list->skip_list.nodes,0,65537UL*
sizeof(*pixel_list->skip_list.nodes));
pixel_list->signature=MagickCoreSignature;
return(pixel_list);
}
static PixelList **AcquirePixelListTLS(const size_t width,
const size_t height)
{
PixelList
**pixel_list;
ssize_t
i;
size_t
number_threads;
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
pixel_list=(PixelList **) AcquireQuantumMemory(number_threads,
sizeof(*pixel_list));
if (pixel_list == (PixelList **) NULL)
return((PixelList **) NULL);
(void) memset(pixel_list,0,number_threads*sizeof(*pixel_list));
for (i=0; i < (ssize_t) number_threads; i++)
{
pixel_list[i]=AcquirePixelList(width,height);
if (pixel_list[i] == (PixelList *) NULL)
return(DestroyPixelListTLS(pixel_list));
}
return(pixel_list);
}
static void AddNodePixelList(PixelList *pixel_list,const size_t color)
{
SkipList
*p;
ssize_t
level;
size_t
search,
update[9];
/*
Initialize the node.
*/
p=(&pixel_list->skip_list);
p->nodes[color].signature=pixel_list->signature;
p->nodes[color].count=1;
/*
Determine where it belongs in the list.
*/
search=65536UL;
(void) memset(update,0,sizeof(update));
for (level=p->level; level >= 0; level--)
{
while (p->nodes[search].next[level] < color)
search=p->nodes[search].next[level];
update[level]=search;
}
/*
Generate a pseudo-random level for this node.
*/
for (level=0; ; level++)
{
pixel_list->seed=(pixel_list->seed*42893621L)+1L;
if ((pixel_list->seed & 0x300) != 0x300)
break;
}
if (level > 8)
level=8;
if (level > (p->level+2))
level=p->level+2;
/*
If we're raising the list's level, link back to the root node.
*/
while (level > p->level)
{
p->level++;
update[p->level]=65536UL;
}
/*
Link the node into the skip-list.
*/
do
{
p->nodes[color].next[level]=p->nodes[update[level]].next[level];
p->nodes[update[level]].next[level]=color;
} while (level-- > 0);
}
static inline void GetMedianPixelList(PixelList *pixel_list,Quantum *pixel)
{
SkipList
*p;
size_t
color;
ssize_t
count;
/*
Find the median value for each of the color.
*/
p=(&pixel_list->skip_list);
color=65536L;
count=0;
do
{
color=p->nodes[color].next[0];
count+=(ssize_t) p->nodes[color].count;
} while (count <= (ssize_t) (pixel_list->length >> 1));
*pixel=ScaleShortToQuantum((unsigned short) color);
}
static inline void GetModePixelList(PixelList *pixel_list,Quantum *pixel)
{
SkipList
*p;
size_t
color,
max_count,
mode;
ssize_t
count;
/*
Make each pixel the 'predominant color' of the specified neighborhood.
*/
p=(&pixel_list->skip_list);
color=65536L;
mode=color;
max_count=p->nodes[mode].count;
count=0;
do
{
color=p->nodes[color].next[0];
if (p->nodes[color].count > max_count)
{
mode=color;
max_count=p->nodes[mode].count;
}
count+=(ssize_t) p->nodes[color].count;
} while (count < (ssize_t) pixel_list->length);
*pixel=ScaleShortToQuantum((unsigned short) mode);
}
static inline void GetNonpeakPixelList(PixelList *pixel_list,Quantum *pixel)
{
SkipList
*p;
size_t
color,
next,
previous;
ssize_t
count;
/*
Finds the non peak value for each of the colors.
*/
p=(&pixel_list->skip_list);
color=65536L;
next=p->nodes[color].next[0];
count=0;
do
{
previous=color;
color=next;
next=p->nodes[color].next[0];
count+=(ssize_t) p->nodes[color].count;
} while (count <= (ssize_t) (pixel_list->length >> 1));
if ((previous == 65536UL) && (next != 65536UL))
color=next;
else
if ((previous != 65536UL) && (next == 65536UL))
color=previous;
*pixel=ScaleShortToQuantum((unsigned short) color);
}
static inline void InsertPixelList(const Quantum pixel,PixelList *pixel_list)
{
size_t
signature;
unsigned short
index;
index=ScaleQuantumToShort(pixel);
signature=pixel_list->skip_list.nodes[index].signature;
if (signature == pixel_list->signature)
{
pixel_list->skip_list.nodes[index].count++;
return;
}
AddNodePixelList(pixel_list,index);
}
static void ResetPixelList(PixelList *pixel_list)
{
int
level;
SkipNode
*root;
SkipList
*p;
/*
Reset the skip-list.
*/
p=(&pixel_list->skip_list);
root=p->nodes+65536UL;
p->level=0;
for (level=0; level < 9; level++)
root->next[level]=65536UL;
pixel_list->seed=pixel_list->signature++;
}
MagickExport Image *StatisticImage(const Image *image,const StatisticType type,
const size_t width,const size_t height,ExceptionInfo *exception)
{
#define StatisticImageTag "Statistic/Image"
CacheView
*image_view,
*statistic_view;
Image
*statistic_image;
MagickBooleanType
status;
MagickOffsetType
progress;
PixelList
**magick_restrict pixel_list;
ssize_t
center,
y;
/*
Initialize statistics image attributes.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (IsEventLogging() != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
statistic_image=CloneImage(image,0,0,MagickTrue,
exception);
if (statistic_image == (Image *) NULL)
return((Image *) NULL);
status=SetImageStorageClass(statistic_image,DirectClass,exception);
if (status == MagickFalse)
{
statistic_image=DestroyImage(statistic_image);
return((Image *) NULL);
}
pixel_list=AcquirePixelListTLS(MagickMax(width,1),MagickMax(height,1));
if (pixel_list == (PixelList **) NULL)
{
statistic_image=DestroyImage(statistic_image);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
/*
Make each pixel the min / max / median / mode / etc. of the neighborhood.
*/
center=(ssize_t) GetPixelChannels(image)*((ssize_t) image->columns+
MagickMax((ssize_t) width,1L))*(MagickMax((ssize_t) height,1)/2L)+(ssize_t)
GetPixelChannels(image)*(MagickMax((ssize_t) width,1L)/2L);
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
statistic_view=AcquireAuthenticCacheView(statistic_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,statistic_image,statistic_image->rows,1)
#endif
for (y=0; y < (ssize_t) statistic_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
const Quantum
*magick_restrict p;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,-((ssize_t) MagickMax(width,1)/2L),y-
(ssize_t) (MagickMax(height,1)/2L),image->columns+MagickMax(width,1),
MagickMax(height,1),exception);
q=QueueCacheViewAuthenticPixels(statistic_view,0,y,statistic_image->columns, 1,exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) statistic_image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
double
area,
maximum,
minimum,
sum,
sum_squared;
Quantum
pixel;
const Quantum
*magick_restrict pixels;
ssize_t
u;
ssize_t
v;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
PixelTrait statistic_traits=GetPixelChannelTraits(statistic_image,
channel);
if (((traits & UpdatePixelTrait) == 0) ||
((statistic_traits & UpdatePixelTrait) == 0))
continue;
if (((statistic_traits & CopyPixelTrait) != 0) ||
(GetPixelWriteMask(image,p) <= (QuantumRange/2)))
{
SetPixelChannel(statistic_image,channel,p[center+i],q);
continue;
}
pixels=p;
area=0.0;
minimum=pixels[i];
maximum=pixels[i];
sum=0.0;
sum_squared=0.0;
ResetPixelList(pixel_list[id]);
for (v=0; v < (ssize_t) MagickMax(height,1); v++)
{
for (u=0; u < (ssize_t) MagickMax(width,1); u++)
{
if ((type == MedianStatistic) || (type == ModeStatistic) ||
(type == NonpeakStatistic))
{
InsertPixelList(pixels[i],pixel_list[id]);
pixels+=(ptrdiff_t) GetPixelChannels(image);
continue;
}
area++;
if ((double) pixels[i] < minimum)
minimum=(double) pixels[i];
if ((double) pixels[i] > maximum)
maximum=(double) pixels[i];
sum+=(double) pixels[i];
sum_squared+=(double) pixels[i]*(double) pixels[i];
pixels+=(ptrdiff_t) GetPixelChannels(image);
}
pixels+=(ptrdiff_t) GetPixelChannels(image)*image->columns;
}
switch (type)
{
case ContrastStatistic:
{
pixel=ClampToQuantum(MagickAbsoluteValue((maximum-minimum)*
MagickSafeReciprocal(maximum+minimum)));
break;
}
case GradientStatistic:
{
pixel=ClampToQuantum(MagickAbsoluteValue(maximum-minimum));
break;
}
case MaximumStatistic:
{
pixel=ClampToQuantum(maximum);
break;
}
case MeanStatistic:
default:
{
pixel=ClampToQuantum(sum/area);
break;
}
case MedianStatistic:
{
GetMedianPixelList(pixel_list[id],&pixel);
break;
}
case MinimumStatistic:
{
pixel=ClampToQuantum(minimum);
break;
}
case ModeStatistic:
{
GetModePixelList(pixel_list[id],&pixel);
break;
}
case NonpeakStatistic:
{
GetNonpeakPixelList(pixel_list[id],&pixel);
break;
}
case RootMeanSquareStatistic:
{
pixel=ClampToQuantum(sqrt(sum_squared/area));
break;
}
case StandardDeviationStatistic:
{
pixel=ClampToQuantum(sqrt(sum_squared/area-(sum/area*sum/area)));
break;
}
}
SetPixelChannel(statistic_image,channel,pixel,q);
}
p+=(ptrdiff_t) GetPixelChannels(image);
q+=(ptrdiff_t) GetPixelChannels(statistic_image);
}
if (SyncCacheViewAuthenticPixels(statistic_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,StatisticImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
statistic_view=DestroyCacheView(statistic_view);
image_view=DestroyCacheView(image_view);
pixel_list=DestroyPixelListTLS(pixel_list);
if (status == MagickFalse)
statistic_image=DestroyImage(statistic_image);
return(statistic_image);
}
Reference in New Issue View Git Blame Copy Permalink