/* [<][>][^][v][top][bottom][index][help] */
DEFINITIONS
This source file includes following definitions.
- MagickAbsoluteValue
- GetImageChannelFeatures
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% FFFFF EEEEE AAA TTTTT U U RRRR EEEEE %
% F E A A T U U R R E %
% FFF EEE AAAAA T U U RRRR EEE %
% F E A A T U U R R E %
% F EEEEE A A T UUU R R EEEEE %
% %
% %
% MagickCore Image Feature Methods %
% %
% Software Design %
% John Cristy %
% July 1992 %
% %
% %
% Copyright 1999-2011 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 %
% %
% http://www.imagemagick.org/script/license.php %
% %
% 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 "magick/studio.h"
#include "magick/property.h"
#include "magick/animate.h"
#include "magick/blob.h"
#include "magick/blob-private.h"
#include "magick/cache.h"
#include "magick/cache-private.h"
#include "magick/cache-view.h"
#include "magick/client.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/composite.h"
#include "magick/composite-private.h"
#include "magick/compress.h"
#include "magick/constitute.h"
#include "magick/deprecate.h"
#include "magick/display.h"
#include "magick/draw.h"
#include "magick/enhance.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/feature.h"
#include "magick/gem.h"
#include "magick/geometry.h"
#include "magick/list.h"
#include "magick/image-private.h"
#include "magick/magic.h"
#include "magick/magick.h"
#include "magick/memory_.h"
#include "magick/module.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/option.h"
#include "magick/paint.h"
#include "magick/pixel-private.h"
#include "magick/profile.h"
#include "magick/quantize.h"
#include "magick/random_.h"
#include "magick/segment.h"
#include "magick/semaphore.h"
#include "magick/signature-private.h"
#include "magick/string_.h"
#include "magick/thread-private.h"
#include "magick/timer.h"
#include "magick/utility.h"
#include "magick/version.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l F e a t u r e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelFeatures() returns features for each channel in the image in
% each of four directions (horizontal, vertical, left and right diagonals)
% for the specified distance. The features include the angular second
% moment, contrast, correlation, sum of squares: variance, inverse difference
% moment, sum average, sum varience, sum entropy, entropy, difference variance,% difference entropy, information measures of correlation 1, information
% measures of correlation 2, and maximum correlation coefficient. You can
% access the red channel contrast, for example, like this:
%
% channel_features=GetImageChannelFeatures(image,1,exception);
% contrast=channel_features[RedChannel].contrast[0];
%
% Use MagickRelinquishMemory() to free the features buffer.
%
% The format of the GetImageChannelFeatures method is:
%
% ChannelFeatures *GetImageChannelFeatures(const Image *image,
% const size_t distance,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o distance: the distance.
%
% o exception: return any errors or warnings in this structure.
%
*/
static inline ssize_t MagickAbsoluteValue(const ssize_t x)
{
if (x < 0)
return(-x);
return(x);
}
MagickExport ChannelFeatures *GetImageChannelFeatures(const Image *image,
const size_t distance,ExceptionInfo *exception)
{
typedef struct _ChannelStatistics
{
DoublePixelPacket
direction[4]; /* horizontal, vertical, left and right diagonals */
} ChannelStatistics;
CacheView
*image_view;
ChannelFeatures
*channel_features;
ChannelStatistics
**cooccurrence,
correlation,
*density_x,
*density_xy,
*density_y,
entropy_x,
entropy_xy,
entropy_xy1,
entropy_xy2,
entropy_y,
mean,
**Q,
*sum,
sum_squares,
variance;
LongPixelPacket
gray,
*grays;
MagickBooleanType
status;
register ssize_t
i;
size_t
length;
ssize_t
y,
z;
unsigned int
number_grays;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((image->columns < (distance+1)) || (image->rows < (distance+1)))
return((ChannelFeatures *) NULL);
length=AllChannels+1UL;
channel_features=(ChannelFeatures *) AcquireQuantumMemory(length,
sizeof(*channel_features));
if (channel_features == (ChannelFeatures *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(channel_features,0,length*
sizeof(*channel_features));
/*
Form grays.
*/
grays=(LongPixelPacket *) AcquireQuantumMemory(MaxMap+1UL,sizeof(*grays));
if (grays == (LongPixelPacket *) NULL)
{
channel_features=(ChannelFeatures *) RelinquishMagickMemory(
channel_features);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(channel_features);
}
for (i=0; i <= (ssize_t) MaxMap; i++)
{
grays[i].red=(~0U);
grays[i].green=(~0U);
grays[i].blue=(~0U);
grays[i].opacity=(~0U);
grays[i].index=(~0U);
}
status=MagickTrue;
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*restrict indexes;
register const PixelPacket
*restrict p;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
grays[ScaleQuantumToMap(p->red)].red=
ScaleQuantumToMap(p->red);
grays[ScaleQuantumToMap(p->green)].green=
ScaleQuantumToMap(p->green);
grays[ScaleQuantumToMap(p->blue)].blue=
ScaleQuantumToMap(p->blue);
if (image->matte != MagickFalse)
grays[ScaleQuantumToMap(p->opacity)].opacity=
ScaleQuantumToMap(p->opacity);
if (image->colorspace == CMYKColorspace)
grays[ScaleQuantumToMap(indexes[x])].index=
ScaleQuantumToMap(indexes[x]);
p++;
}
}
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
{
grays=(LongPixelPacket *) RelinquishMagickMemory(grays);
channel_features=(ChannelFeatures *) RelinquishMagickMemory(
channel_features);
return(channel_features);
}
(void) ResetMagickMemory(&gray,0,sizeof(gray));
for (i=0; i <= (ssize_t) MaxMap; i++)
{
if (grays[i].red != ~0U)
grays[gray.red++].red=grays[i].red;
if (grays[i].green != ~0U)
grays[gray.green++].green=grays[i].green;
if (grays[i].blue != ~0U)
grays[gray.blue++].blue=grays[i].blue;
if (image->matte != MagickFalse)
if (grays[i].opacity != ~0U)
grays[gray.opacity++].opacity=grays[i].opacity;
if (image->colorspace == CMYKColorspace)
if (grays[i].index != ~0U)
grays[gray.index++].index=grays[i].index;
}
/*
Allocate spatial dependence matrix.
*/
number_grays=gray.red;
if (gray.green > number_grays)
number_grays=gray.green;
if (gray.blue > number_grays)
number_grays=gray.blue;
if (image->matte != MagickFalse)
if (gray.opacity > number_grays)
number_grays=gray.opacity;
if (image->colorspace == CMYKColorspace)
if (gray.index > number_grays)
number_grays=gray.index;
cooccurrence=(ChannelStatistics **) AcquireQuantumMemory(number_grays,
sizeof(*cooccurrence));
density_x=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1),
sizeof(*density_x));
density_xy=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1),
sizeof(*density_xy));
density_y=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1),
sizeof(*density_y));
Q=(ChannelStatistics **) AcquireQuantumMemory(number_grays,sizeof(*Q));
sum=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(*sum));
if ((cooccurrence == (ChannelStatistics **) NULL) ||
(density_x == (ChannelStatistics *) NULL) ||
(density_xy == (ChannelStatistics *) NULL) ||
(density_y == (ChannelStatistics *) NULL) ||
(Q == (ChannelStatistics **) NULL) ||
(sum == (ChannelStatistics *) NULL))
{
if (Q != (ChannelStatistics **) NULL)
{
for (i=0; i < (ssize_t) number_grays; i++)
Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
}
if (sum != (ChannelStatistics *) NULL)
sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
if (density_y != (ChannelStatistics *) NULL)
density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
if (density_xy != (ChannelStatistics *) NULL)
density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
if (density_x != (ChannelStatistics *) NULL)
density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
if (cooccurrence != (ChannelStatistics **) NULL)
{
for (i=0; i < (ssize_t) number_grays; i++)
cooccurrence[i]=(ChannelStatistics *)
RelinquishMagickMemory(cooccurrence[i]);
cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(
cooccurrence);
}
grays=(LongPixelPacket *) RelinquishMagickMemory(grays);
channel_features=(ChannelFeatures *) RelinquishMagickMemory(
channel_features);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(channel_features);
}
(void) ResetMagickMemory(&correlation,0,sizeof(correlation));
(void) ResetMagickMemory(density_x,0,2*(number_grays+1)*sizeof(*density_x));
(void) ResetMagickMemory(density_xy,0,2*(number_grays+1)*sizeof(*density_xy));
(void) ResetMagickMemory(density_y,0,2*(number_grays+1)*sizeof(*density_y));
(void) ResetMagickMemory(&mean,0,sizeof(mean));
(void) ResetMagickMemory(sum,0,number_grays*sizeof(*sum));
(void) ResetMagickMemory(&sum_squares,0,sizeof(sum_squares));
(void) ResetMagickMemory(density_xy,0,2*number_grays*sizeof(*density_xy));
(void) ResetMagickMemory(&entropy_x,0,sizeof(entropy_x));
(void) ResetMagickMemory(&entropy_xy,0,sizeof(entropy_xy));
(void) ResetMagickMemory(&entropy_xy1,0,sizeof(entropy_xy1));
(void) ResetMagickMemory(&entropy_xy2,0,sizeof(entropy_xy2));
(void) ResetMagickMemory(&entropy_y,0,sizeof(entropy_y));
(void) ResetMagickMemory(&variance,0,sizeof(variance));
for (i=0; i < (ssize_t) number_grays; i++)
{
cooccurrence[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays,
sizeof(**cooccurrence));
Q[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(**Q));
if ((cooccurrence[i] == (ChannelStatistics *) NULL) ||
(Q[i] == (ChannelStatistics *) NULL))
break;
(void) ResetMagickMemory(cooccurrence[i],0,number_grays*
sizeof(**cooccurrence));
(void) ResetMagickMemory(Q[i],0,number_grays*sizeof(**Q));
}
if (i < (ssize_t) number_grays)
{
for (i--; i >= 0; i--)
{
if (Q[i] != (ChannelStatistics *) NULL)
Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
if (cooccurrence[i] != (ChannelStatistics *) NULL)
cooccurrence[i]=(ChannelStatistics *)
RelinquishMagickMemory(cooccurrence[i]);
}
Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
grays=(LongPixelPacket *) RelinquishMagickMemory(grays);
channel_features=(ChannelFeatures *) RelinquishMagickMemory(
channel_features);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(channel_features);
}
/*
Initialize spatial dependence matrix.
*/
status=MagickTrue;
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*restrict indexes;
register const PixelPacket
*restrict p;
register ssize_t
x;
ssize_t
offset,
u,
v;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,-(ssize_t) distance,y,image->columns+
2*distance,distance+1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
p+=distance;
indexes+=distance;
for (x=0; x < (ssize_t) image->columns; x++)
{
for (i=0; i < 4; i++)
{
switch (i)
{
case 0:
default:
{
/*
Horizontal adjacency.
*/
offset=(ssize_t) distance;
break;
}
case 1:
{
/*
Vertical adjacency.
*/
offset=(ssize_t) (image->columns+2*distance);
break;
}
case 2:
{
/*
Right diagonal adjacency.
*/
offset=(ssize_t) ((image->columns+2*distance)-distance);
break;
}
case 3:
{
/*
Left diagonal adjacency.
*/
offset=(ssize_t) ((image->columns+2*distance)+distance);
break;
}
}
u=0;
v=0;
while (grays[u].red != ScaleQuantumToMap(p->red))
u++;
while (grays[v].red != ScaleQuantumToMap((p+offset)->red))
v++;
cooccurrence[u][v].direction[i].red++;
cooccurrence[v][u].direction[i].red++;
u=0;
v=0;
while (grays[u].green != ScaleQuantumToMap(p->green))
u++;
while (grays[v].green != ScaleQuantumToMap((p+offset)->green))
v++;
cooccurrence[u][v].direction[i].green++;
cooccurrence[v][u].direction[i].green++;
u=0;
v=0;
while (grays[u].blue != ScaleQuantumToMap(p->blue))
u++;
while (grays[v].blue != ScaleQuantumToMap((p+offset)->blue))
v++;
cooccurrence[u][v].direction[i].blue++;
cooccurrence[v][u].direction[i].blue++;
if (image->matte != MagickFalse)
{
u=0;
v=0;
while (grays[u].opacity != ScaleQuantumToMap(p->opacity))
u++;
while (grays[v].opacity != ScaleQuantumToMap((p+offset)->opacity))
v++;
cooccurrence[u][v].direction[i].opacity++;
cooccurrence[v][u].direction[i].opacity++;
}
if (image->colorspace == CMYKColorspace)
{
u=0;
v=0;
while (grays[u].index != ScaleQuantumToMap(indexes[x]))
u++;
while (grays[v].index != ScaleQuantumToMap(indexes[x+offset]))
v++;
cooccurrence[u][v].direction[i].index++;
cooccurrence[v][u].direction[i].index++;
}
}
p++;
}
}
grays=(LongPixelPacket *) RelinquishMagickMemory(grays);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
{
for (i=0; i < (ssize_t) number_grays; i++)
cooccurrence[i]=(ChannelStatistics *)
RelinquishMagickMemory(cooccurrence[i]);
cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
channel_features=(ChannelFeatures *) RelinquishMagickMemory(
channel_features);
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(channel_features);
}
/*
Normalize spatial dependence matrix.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
double
normalize;
switch (i)
{
case 0:
default:
{
/*
Horizontal adjacency.
*/
normalize=2.0*image->rows*(image->columns-distance);
break;
}
case 1:
{
/*
Vertical adjacency.
*/
normalize=2.0*(image->rows-distance)*image->columns;
break;
}
case 2:
{
/*
Right diagonal adjacency.
*/
normalize=2.0*(image->rows-distance)*(image->columns-distance);
break;
}
case 3:
{
/*
Left diagonal adjacency.
*/
normalize=2.0*(image->rows-distance)*(image->columns-distance);
break;
}
}
for (y=0; y < (ssize_t) number_grays; y++)
{
register ssize_t
x;
for (x=0; x < (ssize_t) number_grays; x++)
{
cooccurrence[x][y].direction[i].red/=normalize;
cooccurrence[x][y].direction[i].green/=normalize;
cooccurrence[x][y].direction[i].blue/=normalize;
if (image->matte != MagickFalse)
cooccurrence[x][y].direction[i].opacity/=normalize;
if (image->colorspace == CMYKColorspace)
cooccurrence[x][y].direction[i].index/=normalize;
}
}
}
/*
Compute texture features.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
register ssize_t
y;
for (y=0; y < (ssize_t) number_grays; y++)
{
register ssize_t
x;
for (x=0; x < (ssize_t) number_grays; x++)
{
/*
Angular second moment: measure of homogeneity of the image.
*/
channel_features[RedChannel].angular_second_moment[i]+=
cooccurrence[x][y].direction[i].red*
cooccurrence[x][y].direction[i].red;
channel_features[GreenChannel].angular_second_moment[i]+=
cooccurrence[x][y].direction[i].green*
cooccurrence[x][y].direction[i].green;
channel_features[BlueChannel].angular_second_moment[i]+=
cooccurrence[x][y].direction[i].blue*
cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
channel_features[OpacityChannel].angular_second_moment[i]+=
cooccurrence[x][y].direction[i].opacity*
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
channel_features[BlackChannel].angular_second_moment[i]+=
cooccurrence[x][y].direction[i].index*
cooccurrence[x][y].direction[i].index;
/*
Correlation: measure of linear-dependencies in the image.
*/
sum[y].direction[i].red+=cooccurrence[x][y].direction[i].red;
sum[y].direction[i].green+=cooccurrence[x][y].direction[i].green;
sum[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
sum[y].direction[i].opacity+=cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
sum[y].direction[i].index+=cooccurrence[x][y].direction[i].index;
correlation.direction[i].red+=x*y*cooccurrence[x][y].direction[i].red;
correlation.direction[i].green+=x*y*
cooccurrence[x][y].direction[i].green;
correlation.direction[i].blue+=x*y*
cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
correlation.direction[i].opacity+=x*y*
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
correlation.direction[i].index+=x*y*
cooccurrence[x][y].direction[i].index;
/*
Inverse Difference Moment.
*/
channel_features[RedChannel].inverse_difference_moment[i]+=
cooccurrence[x][y].direction[i].red/((y-x)*(y-x)+1);
channel_features[GreenChannel].inverse_difference_moment[i]+=
cooccurrence[x][y].direction[i].green/((y-x)*(y-x)+1);
channel_features[BlueChannel].inverse_difference_moment[i]+=
cooccurrence[x][y].direction[i].blue/((y-x)*(y-x)+1);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].inverse_difference_moment[i]+=
cooccurrence[x][y].direction[i].opacity/((y-x)*(y-x)+1);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].inverse_difference_moment[i]+=
cooccurrence[x][y].direction[i].index/((y-x)*(y-x)+1);
/*
Sum average.
*/
density_xy[y+x+2].direction[i].red+=
cooccurrence[x][y].direction[i].red;
density_xy[y+x+2].direction[i].green+=
cooccurrence[x][y].direction[i].green;
density_xy[y+x+2].direction[i].blue+=
cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
density_xy[y+x+2].direction[i].opacity+=
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
density_xy[y+x+2].direction[i].index+=
cooccurrence[x][y].direction[i].index;
/*
Entropy.
*/
channel_features[RedChannel].entropy[i]-=
cooccurrence[x][y].direction[i].red*
log10(cooccurrence[x][y].direction[i].red+MagickEpsilon);
channel_features[GreenChannel].entropy[i]-=
cooccurrence[x][y].direction[i].green*
log10(cooccurrence[x][y].direction[i].green+MagickEpsilon);
channel_features[BlueChannel].entropy[i]-=
cooccurrence[x][y].direction[i].blue*
log10(cooccurrence[x][y].direction[i].blue+MagickEpsilon);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].entropy[i]-=
cooccurrence[x][y].direction[i].opacity*
log10(cooccurrence[x][y].direction[i].opacity+MagickEpsilon);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].entropy[i]-=
cooccurrence[x][y].direction[i].index*
log10(cooccurrence[x][y].direction[i].index+MagickEpsilon);
/*
Information Measures of Correlation.
*/
density_x[x].direction[i].red+=cooccurrence[x][y].direction[i].red;
density_x[x].direction[i].green+=cooccurrence[x][y].direction[i].green;
density_x[x].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
density_x[x].direction[i].opacity+=
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
density_x[x].direction[i].index+=
cooccurrence[x][y].direction[i].index;
density_y[y].direction[i].red+=cooccurrence[x][y].direction[i].red;
density_y[y].direction[i].green+=cooccurrence[x][y].direction[i].green;
density_y[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
density_y[y].direction[i].opacity+=
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
density_y[y].direction[i].index+=
cooccurrence[x][y].direction[i].index;
}
mean.direction[i].red+=y*sum[y].direction[i].red;
sum_squares.direction[i].red+=y*y*sum[y].direction[i].red;
mean.direction[i].green+=y*sum[y].direction[i].green;
sum_squares.direction[i].green+=y*y*sum[y].direction[i].green;
mean.direction[i].blue+=y*sum[y].direction[i].blue;
sum_squares.direction[i].blue+=y*y*sum[y].direction[i].blue;
if (image->matte != MagickFalse)
{
mean.direction[i].opacity+=y*sum[y].direction[i].opacity;
sum_squares.direction[i].opacity+=y*y*sum[y].direction[i].opacity;
}
if (image->colorspace == CMYKColorspace)
{
mean.direction[i].index+=y*sum[y].direction[i].index;
sum_squares.direction[i].index+=y*y*sum[y].direction[i].index;
}
}
/*
Correlation: measure of linear-dependencies in the image.
*/
channel_features[RedChannel].correlation[i]=
(correlation.direction[i].red-mean.direction[i].red*
mean.direction[i].red)/(sqrt(sum_squares.direction[i].red-
(mean.direction[i].red*mean.direction[i].red))*sqrt(
sum_squares.direction[i].red-(mean.direction[i].red*
mean.direction[i].red)));
channel_features[GreenChannel].correlation[i]=
(correlation.direction[i].green-mean.direction[i].green*
mean.direction[i].green)/(sqrt(sum_squares.direction[i].green-
(mean.direction[i].green*mean.direction[i].green))*sqrt(
sum_squares.direction[i].green-(mean.direction[i].green*
mean.direction[i].green)));
channel_features[BlueChannel].correlation[i]=
(correlation.direction[i].blue-mean.direction[i].blue*
mean.direction[i].blue)/(sqrt(sum_squares.direction[i].blue-
(mean.direction[i].blue*mean.direction[i].blue))*sqrt(
sum_squares.direction[i].blue-(mean.direction[i].blue*
mean.direction[i].blue)));
if (image->matte != MagickFalse)
channel_features[OpacityChannel].correlation[i]=
(correlation.direction[i].opacity-mean.direction[i].opacity*
mean.direction[i].opacity)/(sqrt(sum_squares.direction[i].opacity-
(mean.direction[i].opacity*mean.direction[i].opacity))*sqrt(
sum_squares.direction[i].opacity-(mean.direction[i].opacity*
mean.direction[i].opacity)));
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].correlation[i]=
(correlation.direction[i].index-mean.direction[i].index*
mean.direction[i].index)/(sqrt(sum_squares.direction[i].index-
(mean.direction[i].index*mean.direction[i].index))*sqrt(
sum_squares.direction[i].index-(mean.direction[i].index*
mean.direction[i].index)));
}
/*
Compute more texture features.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
register ssize_t
x;
for (x=2; x < (ssize_t) (2*number_grays); x++)
{
/*
Sum average.
*/
channel_features[RedChannel].sum_average[i]+=
x*density_xy[x].direction[i].red;
channel_features[GreenChannel].sum_average[i]+=
x*density_xy[x].direction[i].green;
channel_features[BlueChannel].sum_average[i]+=
x*density_xy[x].direction[i].blue;
if (image->matte != MagickFalse)
channel_features[OpacityChannel].sum_average[i]+=
x*density_xy[x].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].sum_average[i]+=
x*density_xy[x].direction[i].index;
/*
Sum entropy.
*/
channel_features[RedChannel].sum_entropy[i]-=
density_xy[x].direction[i].red*
log10(density_xy[x].direction[i].red+MagickEpsilon);
channel_features[GreenChannel].sum_entropy[i]-=
density_xy[x].direction[i].green*
log10(density_xy[x].direction[i].green+MagickEpsilon);
channel_features[BlueChannel].sum_entropy[i]-=
density_xy[x].direction[i].blue*
log10(density_xy[x].direction[i].blue+MagickEpsilon);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].sum_entropy[i]-=
density_xy[x].direction[i].opacity*
log10(density_xy[x].direction[i].opacity+MagickEpsilon);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].sum_entropy[i]-=
density_xy[x].direction[i].index*
log10(density_xy[x].direction[i].index+MagickEpsilon);
/*
Sum variance.
*/
channel_features[RedChannel].sum_variance[i]+=
(x-channel_features[RedChannel].sum_entropy[i])*
(x-channel_features[RedChannel].sum_entropy[i])*
density_xy[x].direction[i].red;
channel_features[GreenChannel].sum_variance[i]+=
(x-channel_features[GreenChannel].sum_entropy[i])*
(x-channel_features[GreenChannel].sum_entropy[i])*
density_xy[x].direction[i].green;
channel_features[BlueChannel].sum_variance[i]+=
(x-channel_features[BlueChannel].sum_entropy[i])*
(x-channel_features[BlueChannel].sum_entropy[i])*
density_xy[x].direction[i].blue;
if (image->matte != MagickFalse)
channel_features[OpacityChannel].sum_variance[i]+=
(x-channel_features[OpacityChannel].sum_entropy[i])*
(x-channel_features[OpacityChannel].sum_entropy[i])*
density_xy[x].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].sum_variance[i]+=
(x-channel_features[IndexChannel].sum_entropy[i])*
(x-channel_features[IndexChannel].sum_entropy[i])*
density_xy[x].direction[i].index;
}
}
/*
Compute more texture features.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
register ssize_t
y;
for (y=0; y < (ssize_t) number_grays; y++)
{
register ssize_t
x;
for (x=0; x < (ssize_t) number_grays; x++)
{
/*
Sum of Squares: Variance
*/
variance.direction[i].red+=(y-mean.direction[i].red+1)*
(y-mean.direction[i].red+1)*cooccurrence[x][y].direction[i].red;
variance.direction[i].green+=(y-mean.direction[i].green+1)*
(y-mean.direction[i].green+1)*cooccurrence[x][y].direction[i].green;
variance.direction[i].blue+=(y-mean.direction[i].blue+1)*
(y-mean.direction[i].blue+1)*cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
variance.direction[i].opacity+=(y-mean.direction[i].opacity+1)*
(y-mean.direction[i].opacity+1)*
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
variance.direction[i].index+=(y-mean.direction[i].index+1)*
(y-mean.direction[i].index+1)*cooccurrence[x][y].direction[i].index;
/*
Sum average / Difference Variance.
*/
density_xy[MagickAbsoluteValue(y-x)].direction[i].red+=
cooccurrence[x][y].direction[i].red;
density_xy[MagickAbsoluteValue(y-x)].direction[i].green+=
cooccurrence[x][y].direction[i].green;
density_xy[MagickAbsoluteValue(y-x)].direction[i].blue+=
cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
density_xy[MagickAbsoluteValue(y-x)].direction[i].opacity+=
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
density_xy[MagickAbsoluteValue(y-x)].direction[i].index+=
cooccurrence[x][y].direction[i].index;
/*
Information Measures of Correlation.
*/
entropy_xy.direction[i].red-=cooccurrence[x][y].direction[i].red*
log10(cooccurrence[x][y].direction[i].red+MagickEpsilon);
entropy_xy.direction[i].green-=cooccurrence[x][y].direction[i].green*
log10(cooccurrence[x][y].direction[i].green+MagickEpsilon);
entropy_xy.direction[i].blue-=cooccurrence[x][y].direction[i].blue*
log10(cooccurrence[x][y].direction[i].blue+MagickEpsilon);
if (image->matte != MagickFalse)
entropy_xy.direction[i].opacity-=
cooccurrence[x][y].direction[i].opacity*log10(
cooccurrence[x][y].direction[i].opacity+MagickEpsilon);
if (image->colorspace == CMYKColorspace)
entropy_xy.direction[i].index-=cooccurrence[x][y].direction[i].index*
log10(cooccurrence[x][y].direction[i].index+MagickEpsilon);
entropy_xy1.direction[i].red-=(cooccurrence[x][y].direction[i].red*
log10(density_x[x].direction[i].red*density_y[y].direction[i].red+
MagickEpsilon));
entropy_xy1.direction[i].green-=(cooccurrence[x][y].direction[i].green*
log10(density_x[x].direction[i].green*density_y[y].direction[i].green+
MagickEpsilon));
entropy_xy1.direction[i].blue-=(cooccurrence[x][y].direction[i].blue*
log10(density_x[x].direction[i].blue*density_y[y].direction[i].blue+
MagickEpsilon));
if (image->matte != MagickFalse)
entropy_xy1.direction[i].opacity-=(
cooccurrence[x][y].direction[i].opacity*log10(
density_x[x].direction[i].opacity*density_y[y].direction[i].opacity+
MagickEpsilon));
if (image->colorspace == CMYKColorspace)
entropy_xy1.direction[i].index-=(
cooccurrence[x][y].direction[i].index*log10(
density_x[x].direction[i].index*density_y[y].direction[i].index+
MagickEpsilon));
entropy_xy2.direction[i].red-=(density_x[x].direction[i].red*
density_y[y].direction[i].red*log10(density_x[x].direction[i].red*
density_y[y].direction[i].red+MagickEpsilon));
entropy_xy2.direction[i].green-=(density_x[x].direction[i].green*
density_y[y].direction[i].green*log10(density_x[x].direction[i].green*
density_y[y].direction[i].green+MagickEpsilon));
entropy_xy2.direction[i].blue-=(density_x[x].direction[i].blue*
density_y[y].direction[i].blue*log10(density_x[x].direction[i].blue*
density_y[y].direction[i].blue+MagickEpsilon));
if (image->matte != MagickFalse)
entropy_xy2.direction[i].opacity-=(density_x[x].direction[i].opacity*
density_y[y].direction[i].opacity*log10(
density_x[x].direction[i].opacity*density_y[y].direction[i].opacity+
MagickEpsilon));
if (image->colorspace == CMYKColorspace)
entropy_xy2.direction[i].index-=(density_x[x].direction[i].index*
density_y[y].direction[i].index*log10(
density_x[x].direction[i].index*density_y[y].direction[i].index+
MagickEpsilon));
}
}
channel_features[RedChannel].variance_sum_of_squares[i]=
variance.direction[i].red;
channel_features[GreenChannel].variance_sum_of_squares[i]=
variance.direction[i].green;
channel_features[BlueChannel].variance_sum_of_squares[i]=
variance.direction[i].blue;
if (image->matte != MagickFalse)
channel_features[RedChannel].variance_sum_of_squares[i]=
variance.direction[i].opacity;
if (image->colorspace == CMYKColorspace)
channel_features[RedChannel].variance_sum_of_squares[i]=
variance.direction[i].index;
}
/*
Compute more texture features.
*/
(void) ResetMagickMemory(&variance,0,sizeof(variance));
(void) ResetMagickMemory(&sum_squares,0,sizeof(sum_squares));
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
register ssize_t
x;
for (x=0; x < (ssize_t) number_grays; x++)
{
/*
Difference variance.
*/
variance.direction[i].red+=density_xy[x].direction[i].red;
variance.direction[i].green+=density_xy[x].direction[i].green;
variance.direction[i].blue+=density_xy[x].direction[i].blue;
if (image->matte != MagickFalse)
variance.direction[i].opacity+=density_xy[x].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
variance.direction[i].index+=density_xy[x].direction[i].index;
sum_squares.direction[i].red+=density_xy[x].direction[i].red*
density_xy[x].direction[i].red;
sum_squares.direction[i].green+=density_xy[x].direction[i].green*
density_xy[x].direction[i].green;
sum_squares.direction[i].blue+=density_xy[x].direction[i].blue*
density_xy[x].direction[i].blue;
if (image->matte != MagickFalse)
sum_squares.direction[i].opacity+=density_xy[x].direction[i].opacity*
density_xy[x].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
sum_squares.direction[i].index+=density_xy[x].direction[i].index*
density_xy[x].direction[i].index;
/*
Difference entropy.
*/
channel_features[RedChannel].difference_entropy[i]-=
density_xy[x].direction[i].red*
log10(density_xy[x].direction[i].red+MagickEpsilon);
channel_features[GreenChannel].difference_entropy[i]-=
density_xy[x].direction[i].green*
log10(density_xy[x].direction[i].green+MagickEpsilon);
channel_features[BlueChannel].difference_entropy[i]-=
density_xy[x].direction[i].blue*
log10(density_xy[x].direction[i].blue+MagickEpsilon);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].difference_entropy[i]-=
density_xy[x].direction[i].opacity*
log10(density_xy[x].direction[i].opacity+MagickEpsilon);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].difference_entropy[i]-=
density_xy[x].direction[i].index*
log10(density_xy[x].direction[i].index+MagickEpsilon);
/*
Information Measures of Correlation.
*/
entropy_x.direction[i].red-=(density_x[x].direction[i].red*
log10(density_x[x].direction[i].red+MagickEpsilon));
entropy_x.direction[i].green-=(density_x[x].direction[i].green*
log10(density_x[x].direction[i].green+MagickEpsilon));
entropy_x.direction[i].blue-=(density_x[x].direction[i].blue*
log10(density_x[x].direction[i].blue+MagickEpsilon));
if (image->matte != MagickFalse)
entropy_x.direction[i].opacity-=(density_x[x].direction[i].opacity*
log10(density_x[x].direction[i].opacity+MagickEpsilon));
if (image->colorspace == CMYKColorspace)
entropy_x.direction[i].index-=(density_x[x].direction[i].index*
log10(density_x[x].direction[i].index+MagickEpsilon));
entropy_y.direction[i].red-=(density_y[y].direction[i].red*
log10(density_y[y].direction[i].red+MagickEpsilon));
entropy_y.direction[i].green-=(density_y[y].direction[i].green*
log10(density_y[y].direction[i].green+MagickEpsilon));
entropy_y.direction[i].blue-=(density_y[y].direction[i].blue*
log10(density_y[y].direction[i].blue+MagickEpsilon));
if (image->matte != MagickFalse)
entropy_y.direction[i].opacity-=(density_y[y].direction[i].opacity*
log10(density_y[y].direction[i].opacity+MagickEpsilon));
if (image->colorspace == CMYKColorspace)
entropy_y.direction[i].index-=(density_y[y].direction[i].index*
log10(density_y[y].direction[i].index+MagickEpsilon));
}
/*
Difference variance.
*/
channel_features[RedChannel].difference_variance[i]=
(((double) number_grays*number_grays*sum_squares.direction[i].red)-
(variance.direction[i].red*variance.direction[i].red))/
((double) number_grays*number_grays*number_grays*number_grays);
channel_features[GreenChannel].difference_variance[i]=
(((double) number_grays*number_grays*sum_squares.direction[i].green)-
(variance.direction[i].green*variance.direction[i].green))/
((double) number_grays*number_grays*number_grays*number_grays);
channel_features[BlueChannel].difference_variance[i]=
(((double) number_grays*number_grays*sum_squares.direction[i].blue)-
(variance.direction[i].blue*variance.direction[i].blue))/
((double) number_grays*number_grays*number_grays*number_grays);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].difference_variance[i]=
(((double) number_grays*number_grays*sum_squares.direction[i].opacity)-
(variance.direction[i].opacity*variance.direction[i].opacity))/
((double) number_grays*number_grays*number_grays*number_grays);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].difference_variance[i]=
(((double) number_grays*number_grays*sum_squares.direction[i].index)-
(variance.direction[i].index*variance.direction[i].index))/
((double) number_grays*number_grays*number_grays*number_grays);
/*
Information Measures of Correlation.
*/
channel_features[RedChannel].measure_of_correlation_1[i]=
(entropy_xy.direction[i].red-entropy_xy1.direction[i].red)/
(entropy_x.direction[i].red > entropy_y.direction[i].red ?
entropy_x.direction[i].red : entropy_y.direction[i].red);
channel_features[GreenChannel].measure_of_correlation_1[i]=
(entropy_xy.direction[i].green-entropy_xy1.direction[i].green)/
(entropy_x.direction[i].green > entropy_y.direction[i].green ?
entropy_x.direction[i].green : entropy_y.direction[i].green);
channel_features[BlueChannel].measure_of_correlation_1[i]=
(entropy_xy.direction[i].blue-entropy_xy1.direction[i].blue)/
(entropy_x.direction[i].blue > entropy_y.direction[i].blue ?
entropy_x.direction[i].blue : entropy_y.direction[i].blue);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].measure_of_correlation_1[i]=
(entropy_xy.direction[i].opacity-entropy_xy1.direction[i].opacity)/
(entropy_x.direction[i].opacity > entropy_y.direction[i].opacity ?
entropy_x.direction[i].opacity : entropy_y.direction[i].opacity);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].measure_of_correlation_1[i]=
(entropy_xy.direction[i].index-entropy_xy1.direction[i].index)/
(entropy_x.direction[i].index > entropy_y.direction[i].index ?
entropy_x.direction[i].index : entropy_y.direction[i].index);
channel_features[RedChannel].measure_of_correlation_2[i]=
(sqrt(fabs(1.0-exp(-2.0*(entropy_xy2.direction[i].red-
entropy_xy.direction[i].red)))));
channel_features[GreenChannel].measure_of_correlation_2[i]=
(sqrt(fabs(1.0-exp(-2.0*(entropy_xy2.direction[i].green-
entropy_xy.direction[i].green)))));
channel_features[BlueChannel].measure_of_correlation_2[i]=
(sqrt(fabs(1.0-exp(-2.0*(entropy_xy2.direction[i].blue-
entropy_xy.direction[i].blue)))));
if (image->matte != MagickFalse)
channel_features[OpacityChannel].measure_of_correlation_2[i]=
(sqrt(fabs(1.0-exp(-2.0*(entropy_xy2.direction[i].opacity-
entropy_xy.direction[i].opacity)))));
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].measure_of_correlation_2[i]=
(sqrt(fabs(1.0-exp(-2.0*(entropy_xy2.direction[i].index-
entropy_xy.direction[i].index)))));
}
/*
Compute more texture features.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (i=0; i < 4; i++)
{
for (z=0; z < (ssize_t) number_grays; z++)
{
register ssize_t
y;
ChannelStatistics
pixel;
(void) ResetMagickMemory(&pixel,0,sizeof(pixel));
for (y=0; y < (ssize_t) number_grays; y++)
{
register ssize_t
x;
for (x=0; x < (ssize_t) number_grays; x++)
{
/*
Contrast: amount of local variations present in an image.
*/
if (((y-x) == z) || ((x-y) == z))
{
pixel.direction[i].red+=cooccurrence[x][y].direction[i].red;
pixel.direction[i].green+=cooccurrence[x][y].direction[i].green;
pixel.direction[i].blue+=cooccurrence[x][y].direction[i].blue;
if (image->matte != MagickFalse)
pixel.direction[i].opacity+=
cooccurrence[x][y].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
pixel.direction[i].index+=cooccurrence[x][y].direction[i].index;
}
/*
Maximum Correlation Coefficient.
*/
Q[z][y].direction[i].red+=cooccurrence[z][x].direction[i].red*
cooccurrence[y][x].direction[i].red/density_x[z].direction[i].red/
density_y[x].direction[i].red;
Q[z][y].direction[i].green+=cooccurrence[z][x].direction[i].green*
cooccurrence[y][x].direction[i].green/
density_x[z].direction[i].green/density_y[x].direction[i].red;
Q[z][y].direction[i].blue+=cooccurrence[z][x].direction[i].blue*
cooccurrence[y][x].direction[i].blue/density_x[z].direction[i].blue/
density_y[x].direction[i].blue;
if (image->matte != MagickFalse)
Q[z][y].direction[i].opacity+=
cooccurrence[z][x].direction[i].opacity*
cooccurrence[y][x].direction[i].opacity/
density_x[z].direction[i].opacity/
density_y[x].direction[i].opacity;
if (image->colorspace == CMYKColorspace)
Q[z][y].direction[i].index+=cooccurrence[z][x].direction[i].index*
cooccurrence[y][x].direction[i].index/
density_x[z].direction[i].index/density_y[x].direction[i].index;
}
}
channel_features[RedChannel].contrast[i]+=z*z*pixel.direction[i].red;
channel_features[GreenChannel].contrast[i]+=z*z*pixel.direction[i].green;
channel_features[BlueChannel].contrast[i]+=z*z*pixel.direction[i].blue;
if (image->matte != MagickFalse)
channel_features[OpacityChannel].contrast[i]+=z*z*
pixel.direction[i].opacity;
if (image->colorspace == CMYKColorspace)
channel_features[BlackChannel].contrast[i]+=z*z*
pixel.direction[i].index;
}
/*
Maximum Correlation Coefficient.
Future: return second largest eigenvalue of Q.
*/
channel_features[RedChannel].maximum_correlation_coefficient[i]=
sqrt((double) -1.0);
channel_features[GreenChannel].maximum_correlation_coefficient[i]=
sqrt((double) -1.0);
channel_features[BlueChannel].maximum_correlation_coefficient[i]=
sqrt((double) -1.0);
if (image->matte != MagickFalse)
channel_features[OpacityChannel].maximum_correlation_coefficient[i]=
sqrt((double) -1.0);
if (image->colorspace == CMYKColorspace)
channel_features[IndexChannel].maximum_correlation_coefficient[i]=
sqrt((double) -1.0);
}
/*
Relinquish resources.
*/
sum=(ChannelStatistics *) RelinquishMagickMemory(sum);
for (i=0; i < (ssize_t) number_grays; i++)
Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]);
Q=(ChannelStatistics **) RelinquishMagickMemory(Q);
density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y);
density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy);
density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x);
for (i=0; i < (ssize_t) number_grays; i++)
cooccurrence[i]=(ChannelStatistics *)
RelinquishMagickMemory(cooccurrence[i]);
cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence);
return(channel_features);
}