//============================================================================ // Name : imagedemo_sym.cpp // Author : Rafat Hussain // Version : // Copyright : // Description : //============================================================================ #include #include #include #include #include #include #include #include "wavelet.h" #include "cv.h" #include "highgui.h" #include "cxcore.h" using namespace std; using namespace cv; void* maxval(vector > &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 &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("Fig10.04(a).jpg"); 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 > vec1(rows, vector(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 = "db3"; vector 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 3 (eg., int e = 3) vector length; vector output,flag; int J =3; int e=3; dwt_2d_sym(vec1,J,nm,output,flag,length,e); double max; vector 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 > dwtdisp(rows_n, vector(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 > dwt_output= dwtdisp; 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 > dwt_hold(rows_n, vector( 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); // Finding IDWT vector > idwt_output(rows, vector(cols)); idwt_2d_sym( output,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( "Reconstructed Image", 1 ); // creation of a visualisation window cvShowImage( "Reconstructed Image", dvImg ); // image visualisation cvWaitKey(); cvDestroyWindow("Reconstructed Image"); cvSaveImage("recon.bmp",dvImg); return 0; }