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/*////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Created By: Riddhish Bhalodia
Date: 14th October 2015
Usage:
void wiener2(Mat img,int n, double sigma)
1) img : Input image, grayscale only
2) n : filt size
3) sigma : noise var, if sigma = 0 then the variance is estimated from data
*/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
#include <numeric>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/opencv.hpp"
#include <iostream>
using namespace cv;
using namespace std;
extern "C"
{
#include "api_scilab.h"
#include "Scierror.h"
#include "BOOL.h"
#include <localization.h>
#include "sciprint.h"
#include "../common.h"
int opencv_wiener2(char *fname, unsigned long fname_len){
SciErr sciErr;
int intErr = 0;
int iRows=0,iCols=0;
int *piAddr = NULL;
int *piAddrNew = NULL;
int *piAddr2 = NULL;
int *piAddr3 = NULL;
double n;
double sigma;
Mat img;
//checking input argument
CheckInputArgument(pvApiCtx, 3, 3);
CheckOutputArgument(pvApiCtx, 1, 1) ;
retrieveImage(img, 1);
//for value of the scale factor
sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2);
if (sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
intErr = getScalarDouble(pvApiCtx, piAddr2, &n);
if(intErr)
{
return intErr;
}
sciErr = getVarAddressFromPosition(pvApiCtx,3,&piAddr3);
if (sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
intErr = getScalarDouble(pvApiCtx, piAddr3, &sigma);
if(intErr)
{
return intErr;
}
// The error checks for the function
if(n != round(n) || n<=0 || int(n)%2==0)
{
sciprint("The value of n must be an odd integer \n");
return 0;
}
Mat out = Mat::zeros(img.size(),img.type());
sigma=255*255*sigma;
if(img.channels() !=1){
sciprint("Grayscale images only!");
return 0;
}
int i_min,i_max,j_min,j_max;
int w = (n-1)/2;
if(sigma==0){
double noise_est = 0;
for(int i=0;i<img.rows;i++){
for(int j=0;j<img.cols;j++){
i_min = max(i-w,0);
i_max = min(i+w,img.rows-1);
j_min = max(j-w,0);
j_max = min(j+w,img.cols-1);
// find mean of the patch
double mean = 0;
for(int ii=i_min;ii<(i_max+1);ii++){
for(int jj=j_min;jj<(j_max+1);jj++){
mean = mean + ((double)img.at<uchar>(ii,jj));
}
}
mean = mean/(n*n);
double var=0;
for(int ii=i_min;ii<(i_max+1);ii++){
for(int jj=j_min;jj<(j_max+1);jj++){
var = var + ((double)img.at<uchar>(ii,jj))*((double)img.at<uchar>(ii,jj));
}
}
var = var/(n*n);
var = var - mean*mean;
noise_est = noise_est + var;
}
}
noise_est = noise_est/(img.rows*img.cols);
sigma = noise_est;
}
for(int i=0;i<img.rows;i++){
for(int j=0;j<img.cols;j++){
i_min = max(i-w,0);
i_max = min(i+w,img.rows-1);
j_min = max(j-w,0);
j_max = min(j+w,img.cols-1);
// find mean of the patch
double mean = 0;
for(int ii=i_min;ii<(i_max+1);ii++){
for(int jj=j_min;jj<(j_max+1);jj++){
mean = mean + ((double)img.at<uchar>(ii,jj));
}
}
mean = mean/(n*n);
// find variance of the patch
double var=0;
for(int ii=i_min;ii<(i_max+1);ii++){
for(int jj=j_min;jj<(j_max+1);jj++){
var = var + ((double)img.at<uchar>(ii,jj))*((double)img.at<uchar>(ii,jj));
}
}
var = var/(n*n);
var = var - mean*mean;
double temp;
double sum=0;
temp = mean + (fmax(0,(var - sigma))/fmax(var,sigma))*(((double)img.at<uchar>(i,j)) - mean);
out.at<uchar>(i,j) = temp;
}
}
// out is the return image
string tempstring = type2str(out.type());
char *checker;
checker = (char *)malloc(tempstring.size() + 1);
memcpy(checker, tempstring.c_str(), tempstring.size() + 1);
returnImage(checker,out,1);
free(checker);
//Assigning the list as the Output Variable
AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1;
ReturnArguments(pvApiCtx);
return 0;
}
}
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