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/** @file */
/* The MIT License
*
* Copyright (c) 2008, Naotoshi Seo <sonots(at)sonots.com>
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef CV_GAUSSNORM_INCLUDED
#define CV_GAUSSNORM_INCLUDED
#include "cv.h"
#include "cvaux.h"
#define _USE_MATH_DEFINES
#include <math.h>
#include "cvmatelemcn.h"
// @todo
// CVAPI(void) cvMatGaussNorm( const CvMat* samples, CvMat* dst );
// #define cvGaussNorm( sample, dst ) cvMatGaussNorm( sample, dst )
// CVAPI(void) cvImgGaussNorm( const IplImage* img, IplImage* normed ) {
// IplImage* sample, samplehdr;
// IplImage* dst, dsthdr;
// sample = cvReshape( img, &samplehdr, 1, img->nChannels );
// dst = cvReshape( normed, &dsthdr, 1, dst->nChannels );
// // make sure how it is reshaped
// cvMatGaussNorm( sample, dst );
// }
/**
* Zero mean and unit covariance normalization of an image
* Each channel is processed independently
*
* @param src input image
* @param dst normalized image. 32F or 64F should be preferred.
*/
CVAPI(void) cvGaussNormImage( const CvArr* src, CvArr* dst )
{
CvMat instub, *in = (CvMat*)src;
CvMat outstub, *out = (CvMat*)dst;
int coi = 0;
CvScalar mean, std;
int rows, cols, nChannels;
int ch, row, col;
CvScalar inval;
CvMat *tmp_in;
CvMat *sub_in;
CV_FUNCNAME( "cvGaussNormImage" );
__CV_BEGIN__;
if( !CV_IS_MAT(in) )
{
CV_CALL( in = cvGetMat( in, &instub, &coi ) );
if (coi != 0) CV_ERROR_FROM_CODE(CV_BadCOI);
}
if( !CV_IS_MAT(out) )
{
CV_CALL( out = cvGetMat( out, &outstub, &coi ) );
if (coi != 0) CV_ERROR_FROM_CODE(CV_BadCOI);
}
CV_ASSERT( in->rows == out->rows && in->cols == out->cols );
CV_ASSERT( CV_MAT_CN(in->type) == CV_MAT_CN(out->type) );
if( in->type != out->type ) {
tmp_in = cvCreateMat( out->rows, out->cols, out->type );
cvConvert( in, tmp_in );
} else {
tmp_in = in;
}
sub_in = cvCreateMat( out->rows, out->cols, out->type );
cvAvgSdv( tmp_in, &mean, &std );
cvSubS( tmp_in, mean, sub_in );
//cvScale( sub_in, out, 1.0/std.val[0] ); // do channel
rows = out->rows;
cols = out->cols;
nChannels = CV_MAT_CN(out->type);
for( row = 0; row < rows; row++ ) {
for( col = 0; col < cols; col++ ) {
inval = cvGet2D( sub_in, row, col );
for( ch = 0; ch < nChannels; ch++ ) {
inval.val[ch] /= std.val[ch];
}
cvSet2D( out, row, col, inval );
}
}
if( in->type != out->type ) {
cvReleaseMat( &tmp_in );
}
cvReleaseMat( &sub_in );
__CV_END__;
}
#endif