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/* laplacian of gaussian
*
* Written on: 30/11/1989
* Updated on: 6/12/1991
* 7/8/96 JC
* - ansified, mem leaks plugged
* 20/11/98 JC
* - mask too large check added
* 26/3/02 JC
* - ahem, was broken since '96, thanks matt
* 16/7/03 JC
* - makes mask out to zero, not out to minimum, thanks again matt
* 22/10/10
* - gtkdoc
*/
/*
This file is part of VIPS.
VIPS is free software; you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
/*
These files are distributed with VIPS - http://www.vips.ecs.soton.ac.uk
*/
/*
#define PIM_RINT 1
*/
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif /*HAVE_CONFIG_H*/
#include <vips/intl.h>
#include <stdio.h>
#include <math.h>
#include <vips/vips.h>
#include <vips/util.h>
#define IM_MAXMASK 256
/**
* im_log_dmask:
* @filename: the returned mask has this set as the filename
* @sigma: standard deviation of mask
* @min_ampl: minimum amplitude
*
* im_log_dmask() creates a circularly symmetric Laplacian of Gaussian mask
* of radius
* @sigma. The size of the mask is determined by the variable @min_ampl;
* if for instance the value .1 is entered this means that the produced mask
* is clipped at values within 10 persent of zero, and where the change
* between mask elements is less than 10%.
*
* The program uses the following equation: (from Handbook of Pattern
* Recognition and image processing by Young and Fu, AP 1986 pages 220-221):
*
* H(r) = (1 / (2 * M_PI * s4)) *
* (2 - (r2 / s2)) *
* exp(-r2 / (2 * s2))
*
* where s2 = sigma * sigma, s4 = s2 * s2, r2 = r * r.
*
* The generated mask has odd size and its maximum value is normalised to 1.0.
*
* See also: im_log_imask(), im_gauss_dmask(), im_conv().
*
* Returns: the calculated mask on success, or NULL on error.
*/
DOUBLEMASK *
im_log_dmask( const char *filename, double sigma, double min_ampl )
{
const double sig2 = sigma * sigma;
double last;
int x, y, k;
double *pt1, *pt2, *pt3, *pt4;
int xm, ym;
int xm2, ym2; /* xm2 = xm/2 */
int offset;
double *cf, *cfs, *mc;
DOUBLEMASK *m;
double sum;
/* Find the size of the mask depending on the entered data. We want to
* eval the mask out to the flat zero part, ie. beyond the minimum and
* to the point where it comes back up towards zero.
*/
last = 0.0;
for( x = 0; x < IM_MAXMASK; x++ ) {
const double distance = x * x;
double val;
/* Handbook of Pattern Recognition and image processing
* by Young and Fu AP 1986 pp 220-221
* temp = (1.0 / (2.0 * IM_PI * sig4)) *
(2.0 - (distance / sig2)) *
exp( (-1.0) * distance / (2.0 * sig2) )
.. use 0.5 to normalise
*/
val = 0.5 *
(2.0 - (distance / sig2)) *
exp( -distance / (2.0 * sig2) );
/* Stop when change in value (ie. difference from the last
* point) is positive (ie. we are going up) and absolute value
* is less than the min.
*/
if( val - last >= 0 &&
fabs( val ) < min_ampl )
break;
last = val;
}
if( x == IM_MAXMASK ) {
im_error( "im_log_dmask", "%s", _( "mask too large" ) );
return( NULL );
}
xm2 = x;
ym2 = x;
xm = xm2 * 2 + 1;
ym = ym2 * 2 + 1;
if( !(cfs = IM_ARRAY( NULL, (xm2 + 1) * (ym2 + 1), double )) )
return( NULL );
/* Make 1/4 of the mask.
*/
for( k = 0, y = 0; y <= ym2; y++ )
for( x = 0; x <= xm2; x++, k++ ) {
const double distance = x * x + y * y;
cfs[k] = 0.5 *
(2.0 - (distance / sig2)) *
exp( -distance / (2.0 * sig2) );
}
#ifdef PIM_RINT
for( k = 0, y = 0; y <= ym2; y++ ) {
for( x = 0; x <= xm2; x++, k++ )
fprintf( stderr, "%3.2f ", cfs[k] );
fprintf( stderr, "\n" );
}
#endif
if( !(m = im_create_dmask( filename, xm, ym )) ) {
im_free( cfs );
return( NULL );
}
/* Copy the 1/4 cfs into the m
*/
cf = cfs;
offset = xm2 * (xm + 1);
mc = m->coeff + offset;
for( y = 0; y <= ym2; y++ ) {
for( x = 0; x <= xm2; x++ ) {
pt1 = mc + (y * xm) + x;
pt2 = mc - (y * xm) + x;
pt3 = mc + (y * xm) - x;
pt4 = mc - (y * xm) - x;
*pt1 = cf[x];
*pt2 = cf[x];
*pt3 = cf[x];
*pt4 = cf[x];
}
cf += (xm2 + 1);
}
im_free( cfs );
sum = 0.0;
for( k = 0, y = 0; y < m->ysize; y++ )
for( x = 0; x < m->xsize; x++, k++ )
sum += m->coeff[k];
m->scale = sum;
m->offset = 0.0;
#ifdef PIM_RINT
im_print_dmask( m );
#endif
return( m );
}
/**
* im_log_imask:
* @filename: the returned mask has this set as the filename
* @sigma: standard deviation of mask
* @min_ampl: minimum amplitude
*
* im_log_imask() works exactly as im_log_dmask(), but the returned mask
* is scaled so that it's maximum value it set to 100.
*
* See also: im_log_dmask(), im_gauss_imask(), im_conv().
*
* Returns: the calculated mask on success, or NULL on error.
*/
INTMASK *
im_log_imask( const char *filename, double sigma, double min_ampl )
{
DOUBLEMASK *dm;
INTMASK *im;
if( !(dm = im_log_dmask( filename, sigma, min_ampl )) )
return( NULL );
if( !(im = im_scale_dmask( dm, dm->filename )) ) {
im_free_dmask( dm );
return( NULL );
}
im_free_dmask( dm );
return( im ) ;
}
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