Image Approximation using symmetric approximation DWT

demo/imagedemo_sym2.cpp

@@ -0,0 +1,322 @@
+//============================================================================
+// Name        : imagedemo_sym.cpp
+// Author      : Rafat Hussain
+// Version     :
+// Copyright   : 
+// Description :
+//============================================================================
+
+#include <iostream>
+#include <fstream>
+#include <vector>
+#include <string>
+#include <complex>
+#include <cmath>
+#include <algorithm>
+#include "wavelet.h"
+#include "cv.h"
+#include "highgui.h"
+#include "cxcore.h"
+
+using namespace std;
+using namespace cv;
+
+void findthresh(vector<double> &vector1, int N, double& t){
+	sort(vector1.begin(), vector1.end(), greater<double>());
+	t = vector1.at(N-1);
+}
+
+void* maxval(vector<vector<double> > &arr, double &max){
+	max = 0;
+	for (unsigned int i =0; i < arr.size(); i++) {
+		for (unsigned int j =0; j < arr[0].size(); j++) {
+			if (max <= arr[i][j]){
+				max = arr[i][j];
+			}
+		}
+	}
+	return 0;
+}
+
+void* maxval1(vector<double> &arr, double &max){
+	max = 0;
+	for (unsigned int i =0; i < arr.size(); i++) {
+		if (max <= arr[i]){
+			max = arr[i];
+		}
+
+	}
+	return 0;
+}
+
+
+int main() {
+	IplImage* img = cvLoadImage("lena512.bmp");
+	if (!img){
+		cout << " Can't read Image. Try Different Format." << endl;
+		exit(1);
+	}
+	int height, width;
+	height = img->height;
+	width = img->width;
+	int nc = img->nChannels;
+	//   uchar* ptr2 =(uchar*) img->imageData;
+	int pix_depth = img->depth;
+	CvSize size;
+	size.width =width;
+	size.height=height;
+	cout << "depth" << pix_depth <<  "Channels" << nc << endl;
+
+
+	cvNamedWindow("Original Image", CV_WINDOW_AUTOSIZE);
+	cvShowImage("Original Image", img);
+	cvWaitKey();
+	cvDestroyWindow("Original Image");
+	cvSaveImage("orig.bmp",img);
+
+
+	int rows =(int) height;
+	int cols =(int) width;
+	Mat matimg(img);
+
+	vector<vector<double> > vec1(rows, vector<double>(cols));
+
+
+	int k =1;
+	for (int i=0; i < rows; i++) {
+		for (int j =0; j < cols; j++){
+			unsigned char temp;
+			temp = ((uchar*) matimg.data + i * matimg.step)[j  * matimg.elemSize() + k ];
+			vec1[i][j] = (double) temp;
+		}
+
+	}
+
+	string nm = "db2";
+	vector<double> l1,h1,l2,h2;
+	filtcoef(nm,l1,h1,l2,h2);
+	// unsigned int lf=l1.size();
+	//  int rows_n =(int) (rows+ J*(lf-1));
+	//  int cols_n =(int)  (cols + J * ( lf -1));
+
+	// Finding 2D DWT Transform of the image using symetric extension algorithm
+	// Extension is set to 0 (eg., int e = 0)
+
+	vector<int> length;
+	vector<double> output,flag;
+	int J =6;
+	int e=0;
+	dwt_2d_sym(vec1,J,nm,output,flag,length,e);
+
+	double max;
+	vector<int> length2;
+	// This algorithm computes DWT of image of any given size. Together with convolution and
+	// subsampling operations it is clear that subsampled images are of different length than
+	// dyadic length images. In order to compute the "effective" size of DWT we do additional
+	// calculations.
+	dwt_output_dim_sym(length,length2,J);
+	// length2 is gives the integer vector that contains the size of subimages that will
+	// combine to form the displayed output image. The last two entries of length2 gives the
+	// size of DWT ( rows_n by cols_n)
+
+	int siz = length2.size();
+	int rows_n=length2[siz-2];
+	int cols_n = length2[siz-1];
+
+	vector<vector< double> > dwtdisp(rows_n, vector<double>(cols_n));
+	dispDWT(output,dwtdisp, length ,length2, J);
+
+	// dispDWT returns the 2D object dwtdisp which will be displayed using OPENCV's image
+	// handling functions
+
+	vector<vector<double> >  dwt_output= dwtdisp;
+
+	// Stroing the DWT coefficients in two different vectors that will be used to approximate
+	// Image with two different sets of chosen coefficients.
+
+	vector<double> dwt_coef1;
+	vector<double> dwt_coef2;
+
+	dwt_coef1 = output;
+	dwt_coef2 = output;
+
+	maxval(dwt_output,max);// max value is needed to take care of overflow which happens because
+	// of convolution operations performed on unsigned 8 bit images
+
+	//Displaying Scaled Image
+	// Creating Image in OPENCV
+	IplImage *cvImg; // image used for output
+	CvSize imgSize; // size of output image
+
+	imgSize.width = cols_n;
+	imgSize.height = rows_n;
+
+	cvImg = cvCreateImage( imgSize, 8, 1 );
+	// dwt_hold is created to hold the dwt output as further operations need to be
+	// carried out on dwt_output in order to display scaled images.
+	vector<vector<double> > dwt_hold(rows_n, vector<double>( cols_n));
+	dwt_hold = dwt_output;
+	// Setting coefficients of created image to the scaled DWT output values
+	for (int i = 0; i < imgSize.height; i++ ) {
+		for (int j = 0; j < imgSize.width; j++ ){
+			if ( dwt_output[i][j] <= 0.0){
+				dwt_output[i][j] = 0.0;
+			}
+			if ( i <= (length2[0]) && j <= (length2[1]) ) {
+				((uchar*)(cvImg->imageData + cvImg->widthStep*i))[j] =
+						(char) ( (dwt_output[i][j] / max) * 255.0);
+			} else {
+				((uchar*)(cvImg->imageData + cvImg->widthStep*i))[j] =
+						(char) (dwt_output[i][j]) ;
+			}
+		}
+	}
+
+	cvNamedWindow( "DWT Image", 1 ); // creation of a visualisation window
+	cvShowImage( "DWT Image", cvImg ); // image visualisation
+	cvWaitKey();
+	cvDestroyWindow("DWT Image");
+	cvSaveImage("dwt.bmp",cvImg);
+
+	 // Case 1 : Only 10% of the largest coefficients are considered
+
+	          // Output is the 1D DWT vector
+
+	          int n_coef1= int (output.size()/ 10);
+	          cout << n_coef1 << endl;
+
+	          // Finding Threshold Value corresponding to n_coef1
+
+	          vector<double> temp1;
+	             cout << "size: " << (int) temp1.size() << "\n";
+	             cout << "capacity: " << (int) temp1.capacity() << "\n";
+	             cout << "max_size: " << (int) temp1.max_size() << "\n";
+	             for (unsigned int i =0; i < dwt_coef1.size(); i++) {
+	           		  double tempval = abs(dwt_coef1[i]);
+	           		  temp1.push_back(tempval);
+
+	             }
+
+	             double thresh1= 0.0;
+	             findthresh(temp1,n_coef1,thresh1);
+	             cout << "thresh" << thresh1 << endl;
+
+	             ofstream temp("temp.txt");
+	                       for (unsigned int i =0; i < temp1.size(); i++){
+	                     	  temp << temp1[i] << " " ;
+	                       }
+
+	             // Reset coeffficients value depending on threshold value
+
+
+	             for (unsigned int i =0; i < dwt_coef1.size(); i++) {
+	       		    	double temp = abs(dwt_coef1[i]);
+
+	       		    	if (temp < thresh1){
+	       		    		dwt_coef1.at(i)= 0.0;
+
+	       		    	}
+
+	           	  }
+
+
+	// Finding IDWT
+
+	vector<vector<double> > idwt_output(rows, vector<double>(cols));
+
+	idwt_2d_sym( dwt_coef1,flag, nm, idwt_output,length);
+
+
+
+	//Displaying Reconstructed Image
+
+	IplImage *dvImg;
+	CvSize dvSize; // size of output image
+
+	dvSize.width = idwt_output[0].size();
+	dvSize.height = idwt_output.size();
+
+	cout << idwt_output.size() << idwt_output[0].size() << endl;
+	dvImg = cvCreateImage( dvSize, 8, 1 );
+
+	for (int i = 0; i < dvSize.height; i++ )
+		for (int j = 0; j < dvSize.width; j++ )
+			((uchar*)(dvImg->imageData + dvImg->widthStep*i))[j] =
+					(char) (idwt_output[i][j])  ;
+
+	cvNamedWindow( "10% Coeff Reconstructed Image", 1 ); // creation of a visualisation window
+	cvShowImage( "10% Coeff Reconstructed Image", dvImg ); // image visualisation
+	cvWaitKey();
+	cvDestroyWindow("10% Coeff Reconstructed Image");
+	cvSaveImage("recon.bmp",dvImg);
+
+
+	 // Case 2 : Only 2% of the largest coefficients are considered
+
+		          // Output is the 1D DWT vector
+
+		          int n_coef2= int (output.size()/ 50);
+		          cout << n_coef2 << endl;
+
+		          // Finding Threshold Value corresponding to n_coef1
+
+		          vector<double> temp2;
+
+		             for (unsigned int i =0; i < dwt_coef2.size(); i++) {
+		           		  double tempval = abs(dwt_coef2[i]);
+		           		  temp2.push_back(tempval);
+
+		             }
+
+		             double thresh2= 0.0;
+		             findthresh(temp2,n_coef2,thresh2);
+		             cout << "thresh" << thresh2 << endl;
+
+
+		             // Reset coeffficients value depending on threshold value
+
+
+		             for (unsigned int i =0; i < dwt_coef2.size(); i++) {
+		       		    	double temp = abs(dwt_coef2[i]);
+
+		       		    	if (temp < thresh2){
+		       		    		dwt_coef2.at(i)= 0.0;
+
+		       		    	}
+
+		           	  }
+
+
+		// Finding IDWT
+
+		vector<vector<double> > idwt_output2(rows, vector<double>(cols));
+
+		idwt_2d_sym( dwt_coef2,flag, nm, idwt_output2,length);
+
+
+
+		//Displaying Reconstructed Image
+
+		IplImage *dvImg2;
+		CvSize dvSize2; // size of output image
+
+		dvSize2.width = idwt_output2[0].size();
+		dvSize2.height = idwt_output2.size();
+
+		cout << idwt_output2.size() << idwt_output2[0].size() << endl;
+		dvImg2 = cvCreateImage( dvSize2, 8, 1 );
+
+		for (int i = 0; i < dvSize2.height; i++ )
+			for (int j = 0; j < dvSize2.width; j++ )
+				((uchar*)(dvImg2->imageData + dvImg2->widthStep*i))[j] =
+						(char) (idwt_output2[i][j])  ;
+
+		cvNamedWindow( "2% Coeff Reconstructed Image", 1 ); // creation of a visualisation window
+		cvShowImage( "2% Coeff Reconstructed Image", dvImg2 ); // image visualisation
+		cvWaitKey();
+		cvDestroyWindow("2% Coeff Reconstructed Image");
+		cvSaveImage("recon2.bmp",dvImg2);
+
+
+	return 0;
+}