First CommitHEADmaster

1 files changed, 178 insertions, 0 deletions

diff --git a/sci_gateway/cpp/opencv_wiener2.cpp b/sci_gateway/cpp/opencv_wiener2.cpp
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+++ b/sci_gateway/cpp/opencv_wiener2.cpp
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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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