对图像进行Jpeg压缩进行模拟

#include <iostream>
#include <opencv2\opencv.hpp>
#include <math.h>
using namespace std;
using namespace cv;
int round(double c){
return int(c+0.5*(c<0?-1:1));
}
int main()
{
IplImage *lena=cvLoadImage("lena.bmp");
IplImage *grayImage=cvCreateImage(cvSize(lena->width,lena->height),lena->depth,1);
IplImage *resultImage=cvCreateImage(cvSize(lena->width,lena->height),lena->depth,1);
cvCvtColor(lena,grayImage,CV_BGR2GRAY);
CvMat *grayMat=cvCreateMat(grayImage->height,grayImage->width,CV_64FC1);
CvMat *temp=cvCreateMat(grayImage->height,grayImage->width,CV_64FC1);
CvMat *grayDctMat=cvCreateMat(grayImage->height,grayImage->width,CV_64FC1);
CvMat *quantizationMat=cvCreateMat(grayImage->height,grayImage->width,CV_64FC1);
cvScale(grayImage,grayMat);
//每个像素减去128
for(int i=0;i<grayMat->rows;i++)
{
for (int j=0;j<grayMat->cols;j++)
{
double a=cvmGet(grayMat,i,j);
double b=a-128;
cvmSet(temp,i,j,b);
}
}
//DCT变换
cvDCT(temp,grayDctMat,CV_DXT_FORWARD);
/*
for(int i=0;i<8;i++)
{
for (int j=0;j<8;j++)
{
cout<<grayMat->data.db[i*grayMat->rows+j]<<" ";
}
cout<<endl;
}
cout<<"---------------------------------------------"<<endl;
*/
//量化矩阵
double quantizationData[]={16,11,10,16,24,40,51,61,12,12,14,19,26,58,60,55,14,13,16,24,40,57,69,56,14,17,22,29,51,87,80,62,18,22,37,56,68,109,
103,77,24,35,55,64,81,104,113,92,49,64,78,87,103,121,120,101,72,92,95,98,112,100,103,99};
CvMat quantizationMatrix=cvMat(8,8,CV_64FC1,quantizationData);
//量化过程
for (int i=0;i<32;i++){
for (int j=0;j<32;j++){
for(int m=0;m<8;m++){
for (int n=0;n<8;n++)
{
//量化
double a=cvGetReal2D(grayDctMat,i*8+m,j*8+n);
double b=cvGetReal2D(&quantizationMatrix,m,n);
int c=round(a/b);
//反量化
int d=int(b*c);
cvmSet(quantizationMat,i*8+m,j*8+n,d);
}
}
}
}
//逆DCT变换
cvDCT(quantizationMat,temp,CV_DXT_INVERSE);
for(int i=0;i<temp->rows;i++)
{
for (int j=0;j<temp->cols;j++)
{
double a=cvmGet(temp,i,j);
double b=round(a)+128;
cvmSet(temp,i,j,b);
}
}
cvScale(grayMat,resultImage);
//计算均方误差
double MSE=0;
double square=0;
double PSNR=0;
for(int i=0;i<grayMat->rows;i++)
{
for (int j=0;j<grayMat->cols;j++)
{
double a=cvmGet(grayMat,i,j);
double b=cvmGet(temp,i,j);;
double c=a-b;
//	cout<<c<<endl;
square+=c*c;
}
}
square/=256;
square/=256;
MSE=sqrt(square);
PSNR=10*log10(255*255/MSE);
//	cout<<"square:"<<square<<endl;
cout<<"MSE:"<<MSE<<endl;
cout<<"PSNR:"<<PSNR<<endl;
/*
for(int i=0;i<8;i++)
{
for (int j=0;j<8;j++)
{
cout<<grayMat->data.db[i*grayMat->rows+j]<<" ";
}
cout<<endl;
}*/
/*
for(int i=0;i<quantizationMatrix.rows;i++)
{
for (int j=0;j<quantizationMatrix.cols;j++)
{
cout<<quantizationMatrix.data.db[i*quantizationMatrix.rows+j]<<" ";
}
cout<<endl;
}*/
/*
for (int i=0;i<20;i++)
{
for (int j=0;j<8;j++)
{
cout<<grayMat->data.db[i*grayMat->rows+j]<<" ";
}
cout<<endl;
for (int j=0;j<8;j++)
{
cout<<grayDctMat->data.db[i*grayDctMat->rows+j]<<" ";
}
cout<<endl;
}*/

cvNamedWindow("gray");
cvShowImage("gray",grayImage);
cvNamedWindow("jpeg");
cvShowImage("jpeg",resultImage);
cvWaitKey(0);
cvDestroyWindow("gray");
cvDestroyWindow("jpeg");
cvReleaseImage(&grayImage);
cvReleaseImage(&lena);
getchar();
return 0;
}