yuv.rar_GBIM_jpeg encoder_yuv jpeg

#include <stdio.h> #include <iostream.h> #include <math.h> #define cif #ifdef qcif #define Y_WIDTH 176 #define Y_HEIGHT 144 #define U_WIDTH 88 #define U_HEIGHT 72 #define V_WIDTH 88 #define V_HEIGHT 72 #endif #ifdef cif #define Y_WIDTH 720 #define Y_HEIGHT 576 #define U_WIDTH 720 #define U_HEIGHT 576 #define V_WIDTH 720 #define V_HEIGHT 576 #endif void ReadImage(unsigned char *pImage,char *cFileName,int nWidth,int nHeight,long offset); float snr[Y_HEIGHT/16][Y_WIDTH/16]; double GBIM( int **pImage); unsigned char Y_space1[Y_WIDTH*Y_HEIGHT]; unsigned char Y_space2[Y_WIDTH*Y_HEIGHT]; //unsigned char U_space[U_WIDTH*U_HEIGHT]; //unsigned char V_space[V_WIDTH*V_HEIGHT]; void main() {int i,j,u,v; int imageno; long origin; int diff_y,diftemp; int ** Y_value; Y_value = new int * [Y_HEIGHT]; double GBIM_value[26]; double ave=0; for(i=0;i<Y_HEIGHT;i++) { Y_value[i] = new int[Y_WIDTH]; } for (imageno=1;imageno<26;imageno++) { origin=(imageno-1)*(Y_WIDTH*Y_HEIGHT+U_WIDTH*U_HEIGHT+V_WIDTH*V_HEIGHT); ReadImage(Y_space2,"G:\cif_data\\test_rec16.yuv",Y_WIDTH,Y_HEIGHT,origin); //将Y分量存储为二维数组，以便后面操作 for(int m=0;m<Y_HEIGHT;m++) { for(int n=0;n<Y_WIDTH;n++) Y_value[m][n]=Y_space2[m*Y_WIDTH+n]; } //GBIM块效应估计值 GBIM_value[imageno] = GBIM(Y_value); //cout<<GBIM_value[imageno]<<endl; ave+=GBIM_value[imageno]; } ave=ave/25; cout<<ave<<endl; } void ReadImage(unsigned char *pImage,char *cFileName,int nWidth,int nHeight,long offset) { int j,i; unsigned char *pWork; FILE *fp=0; if ( fp=fopen(cFileName,"rb" ) ) //打开一幅图像 { fseek(fp,offset,SEEK_SET); //文件定位 pWork=pImage; //指针指向 for ( j=0;j<nHeight;j++,pWork+=nWidth ) for ( i=0;i<nWidth;i++ ) fread(pWork+i,1,1,fp); //顺序读取 fclose(fp); } } //GBIM方法估计块效应 double GBIM( int **I) { int nWidth=Y_WIDTH; int nHeight=Y_HEIGHT; int i,j,k,n; int I_trans[Y_WIDTH][Y_HEIGHT]; double Weighted_Value_v=0; double Weighted_Value=0; double Weighted_Value_interpixel=0; double M_hor=0; double M_ver=0; double M_image=0; //水平块效应估计 for (k=1;k<=nWidth/8-1;k++) { for (i=0;i<nHeight;i++) { double Local_mean=0; double Local_mean_left=0; double Local_mean_right=0; double Local_activity=0; double Local_activity_left=0; double Local_activity_right=0; double Weight; //求左右临块的亮度均值 for(n=k*8-8;n<=k*8-1;n++) { Local_mean_left+=I[i][n]/8; } for(n=k*8;n<=k*8+7;n++) { Local_mean_right+=I[i][n]/8; } Local_mean=(Local_mean_left+Local_mean_right)/2; //求左右临块的亮度变化值 for(n=k*8-8;n<=k*8-1;n++) { Local_activity_left+=(I[i][n]-Local_mean_left)*(I[i][n]-Local_mean_left)/8; } for(n=k*8;n<=k*8+7;n++) { Local_activity_right+=(I[i][n]-Local_mean_right)*(I[i][n]-Local_mean_right)/8; } Local_activity=(sqrt(Local_activity_left)+sqrt(Local_activity_right))/2; //求权值系数 if (Local_mean<=81) { Weight=1.15201*log(1+(sqrt(Local_mean)/(1+Local_activity))); } else { Weight=log(1+(sqrt(255-Local_mean)/(1+Local_activity))); } Weighted_Value_v = Weight*(I[i][k*8-1]-I[i][k*8]); Weighted_Value += Weighted_Value_v*Weighted_Value_v; for(int m =1;m<=7;m++) {Weighted_Value_interpixel += (Weight*(I[i][k*8+m-1]-I[i][k*8+m]))*(Weight*(I[i][k*8+m-1]-I[i][k*8+m]));} } } M_hor=sqrt(Weighted_Value)/sqrt(Weighted_Value_interpixel)*7; Weighted_Value=0; Weighted_Value_interpixel=0; //图像存储矩阵转置 for (j=0;j<nHeight;j++) { for (i=0;i<nWidth;i++) { I_trans[i][j]=I[j][i]; } } //竖直块效应估计 for (k=1;k<=nHeight/8-1;k++) { for (i=0;i<nWidth;i++) { double Local_mean=0; double Local_mean_left=0; double Local_mean_right=0; double Local_activity=0; double Local_activity_left=0; double Local_activity_right=0; double Weight=0; //求左右临块的亮度均值 for(n=k*8-8;n<=k*8-1;n++) { Local_mean_left+=I_trans[i][n]/8; } for(n=k*8;n<=k*8+7;n++) { Local_mean_right+=I_trans[i][n]/8; } Local_mean=(Local_mean_left+Local_mean_right)/2; //求左右临块的亮度变化值 for(n=k*8-8;n<=k*8-1;n++) { Local_activity_left+=(I_trans[i][n]-Local_mean_left)*(I_trans[i][n]-Local_mean_left)/8; } for(n=k*8;n<=k*8+7;n++) { Local_activity_right+=(I_trans[i][n]-Local_mean_right)*(I_trans[i][n]-Local_mean_right)/8; } Local_activity=(sqrt(Local_activity_left)+sqrt(Local_activity_right))/2; //求权值系数 if (Local_mean<=81) { Weight=1.15201*log(1+(sqrt(Local_mean)/(1+Local_activity))); } else { Weight=log(1+(sqrt(255-Local_mean)/(1+Local_activity))); } Weighted_Value+=(Weight*(I_trans[i][k*8-1]-I_trans[i][k*8]))*(Weight*(I_trans[i][k*8-1]-I_trans[i][k*8])); for(int m=1;m<=7;m++) {Weighted_Value_interpixel+=(Weight*(I_trans[i][k*8+m-1]-I_trans[i][k*8+m]))*(Weight*(I_trans[i][k*8+m-1]-I_trans[i][k*8+m]));} } } M_ver=sqrt(Weighted_Value)/sqrt(Weighted_Value_interpixel)*7; //图像块效应估计值 M_image=(M_hor+M_ver)/2; return (M_image); }