0

我尝试了下面的代码来查找图像的 DWT 分解。但是我没有包含头文件。而且我认为我没有以恰当的方式运行它。谁能帮我运行这段代码。

这是使用 opencv 2.3.1 的 C++ 代码，操作系统是 ubuntu

#include <iostream>
#include <fstream>
#include <vector>
#include <string>
#include <complex>
#include <cmath>
#include <algorithm>
#include "wavelet2d.h"
#include "cv.h"
#include "highgui.h"
#include "cxcore.h"

using namespace std;
using namespace cv;

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("snow.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<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 = "db3";
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 3 (eg., int e = 3)

vector<int> length;
vector<double> output,flag;
int J =3;
dwt_2d_sym(vec1,J,nm,output,flag,length);

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;

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);

// Finding IDWT

vector<vector<double> > idwt_output(rows, vector<double>(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;
}
4

0 回答 0