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