Evaluate Video Quality

How to evaluate video?
PSNR and SSIM.
PSNR is easy to calculate:

http://blog.csdn.net/c602273091/article/details/49861817

SSIM is more relevant to eye visibility.

How to calculate them?

Using Evalvid.

http://www2.tkn.tu-berlin.de/research/evalvid/
http://download.csdn.net/detail/leixiaohua1020/6374037

Run in cmd or using batching processing.

psnr.exe 1920 1080 420 src.yuv des.yuv > psnr.txt

MSU Video Quality Measurement Tool

http://www.compression.ru/video/quality_measure/video_measurement_tool_en.html

Source Code
From the code below, we can learn how to calculate ssim and psnr and some skills about VS.
Python Version will be displayed in next blog.

#include <math.h>#include <stdio.h>#include <stdlib.h>#include <string.h>#include <time.h>#ifdef _WIN32  #include "stdint_w32.h"  #define alloca _alloca#else  #include <stdint.h>#endif/**************************************************************************** * structural similarity metric [from x264] ****************************************************************************/#define x264_alloca(x) (void*)(((intptr_t)alloca((x)+15)+15)&~15)#define XCHG(type,a,b) { type t = a; a = b; b = t; }#define X264_MIN(a,b) ( (a)<(b) ? (a) : (b) )static void ssim_4x4x2_core( const uint8_t *pix1, int stride1,                             const uint8_t *pix2, int stride2,                             int sums[2][4]){    int x, y, z;    for(z=0; z<2; z++)    {        uint32_t s1=0, s2=0, ss=0, s12=0;        for(y=0; y<4; y++)            for(x=0; x<4; x++)            {                int a = pix1[x+y*stride1];                int b = pix2[x+y*stride2];                s1  += a;                s2  += b;                ss  += a*a;                ss  += b*b;                s12 += a*b;            }        sums[z][0] = s1;        sums[z][1] = s2;        sums[z][2] = ss;        sums[z][3] = s12;        pix1 += 4;        pix2 += 4;    }}static float ssim_end1( int s1, int s2, int ss, int s12 ){    static const int ssim_c1 = (int)(.01*.01*255*255*64 + .5);    static const int ssim_c2 = (int)(.03*.03*255*255*64*63 + .5);    int vars = ss*64 - s1*s1 - s2*s2;    int covar = s12*64 - s1*s2;    return (float)(2*s1*s2 + ssim_c1) * (float)(2*covar + ssim_c2)\           / ((float)(s1*s1 + s2*s2 + ssim_c1) * (float)(vars + ssim_c2));}static float ssim_end4( int sum0[5][4], int sum1[5][4], int width ){    int i;    float ssim = 0.0;    for( i = 0; i < width; i++ )        ssim += ssim_end1( sum0[i][0] + sum0[i+1][0] + sum1[i][0] + sum1[i+1][0],                           sum0[i][1] + sum0[i+1][1] + sum1[i][1] + sum1[i+1][1],                           sum0[i][2] + sum0[i+1][2] + sum1[i][2] + sum1[i+1][2],                           sum0[i][3] + sum0[i+1][3] + sum1[i][3] + sum1[i+1][3] );    return ssim;}float x264_pixel_ssim_wxh(uint8_t *pix1, int stride1, uint8_t *pix2, int stride2, int width, int height ){    int x, y, z;    float ssim = 0.0;    int (*sum0)[4] = x264_alloca(4 * (width/4+3) * sizeof(int));    int (*sum1)[4] = x264_alloca(4 * (width/4+3) * sizeof(int));    width >>= 2;    height >>= 2;    z = 0;    for( y = 1; y < height; y++ )    {        for( ; z <= y; z++ )        {            XCHG( void*, sum0, sum1 );            for( x = 0; x < width; x+=2 )                ssim_4x4x2_core( &pix1[4*(x+z*stride1)], stride1, &pix2[4*(x+z*stride2)], stride2, &sum0[x] );        }        for( x = 0; x < width-1; x += 4 )            ssim += ssim_end4( sum0+x, sum1+x, X264_MIN(4,width-x-1) );    }    return ssim / ((width-1) * (height-1));}int main(int n, char *cl[]){  FILE *f1, *f2;  int ssim = 0, i, x, y, yuv, inc = 1, size = 0, N = 0, Y, F;  double yrmse, diff, mean = 0, stdv = 0, *ypsnr = 0;  unsigned char *b1, *b2;  clock_t t = clock();  if (n != 6 && n != 7) {    puts("psnr x y <YUV format> <src.yuv> <dst.yuv> [multiplex] [ssim]");    puts("  x\t\tframe width");    puts("  y\t\tframe height");    puts("  YUV format\t420, 422, etc.");    puts("  src.yuv\tsource video");    puts("  dst.yuv\tdistorted video");    puts("  [multiplex]\toptional");    puts("  [ssim]\toptional: calculate structural similarity instead of PSNR");    return EXIT_FAILURE;  }  if ((f1 = fopen(cl[4], "rb")) == 0) goto A;  if ((f2 = fopen(cl[5], "rb")) == 0) goto B;  if (!(x = strtoul(cl[1], 0, 10)) ||      !(y = strtoul(cl[2], 0, 10))) goto C;   if ((yuv = strtoul(cl[3], 0, 10)) > 444) goto D;  if (cl[6] && !strcmp(cl[6], "multiplex")) inc = 2;  if (cl[6] && !strcmp(cl[6], "ssim")) ssim = 1;  Y = x * y;  switch (yuv) {    case 400: F = Y; break;    case 422: F = Y * 2; break;    case 444: F = Y * 3; break;    default :    case 420: F = Y * 3 / 2; break;  }  if (!(b1 = malloc(F))) goto E;  if (!(b2 = malloc(F))) goto E;  for (;;) {    if (1 != fread(b1, F, 1, f1) || 1 != fread(b2, F, 1, f2)) break;    if (++N > size) {      size += 0xffff;      if (!(ypsnr = realloc(ypsnr, size * sizeof *ypsnr))) goto E;    }    if (ssim) {      mean += ypsnr[N - 1] = x264_pixel_ssim_wxh(b1, x, b2, x, x, y);    } else {      for (yrmse = 0, i = inc - 1; i < (inc == 1 ? Y : F); i += inc) {        diff = b1[i] - b2[i];        yrmse += diff * diff;      }      mean += ypsnr[N - 1] = yrmse ? 20 * (log10(255 / sqrt(yrmse / Y))) : 0;    }    printf("%.3f\n", ypsnr[N - 1]);  }  if (N) {    mean /= N;    for (stdv = 0, i = 0; i < N; i++) {      diff = ypsnr[i] - mean;      stdv += diff * diff;    }    stdv = sqrt(stdv / (N - 1));    free(ypsnr);  }    fclose(f1);    fclose(f2);    fprintf(stderr, "%s:\t%d frames (CPU: %lu s) mean: %.2f stdv: %.2f\n",    ssim ? "ssim" : "psnr", N, (unsigned long) ((clock() - t) / CLOCKS_PER_SEC), mean, stdv);    return 0;    A: fprintf(stderr, " Error opening source video file.\n"); goto X;    B: fprintf(stderr, " Error opening decoded video file.\n"); goto X;    C: fprintf(stderr, " Invalid width or height.\n"); goto X;    D: fprintf(stderr, " Invalid YUV format.\n"); goto X;    E: fprintf(stderr, " Not enough memory.\n");    X: return EXIT_FAILURE;}

Standard of Video Evaluation

http://download.csdn.net/detail/leixiaohua1020/6423425

Conclusion of Evaluation Method
PeakSignal to Noise Ratio(PSNR)
Ref to my ex-blog.
noise quality measure (NQM) index
Ref：N. Damera-Venkata, T.D. Kite, W.S. Geisler, B.L. Evans, and A.C.Bovik, “Image quality assessment based on a degradation model,” IEEE Trans. IP,vol. 9, pp. 636-650, 2000.
universal quality index (UQI)
Ref：Z. Wang and A.C. Bovik, “A universal image quality index,” IEEE SignalProcess. Lett., vol. 9, pp. 81-84, 2002.
structural similarity (SSIM) index
Ref：Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli,”Image qualityassessment: from error visibility to structural similarity,” IEEE Trans. IP,vol. 13, pp. 600-612, 2004.
multi-scaleSSIM (MS-SSIM) index
Ref：Z. Wang, E.P. Simoncelli, and A.C. Bovik, “Multi-scale structuralsimilarity for image quality assessment,” ACSSC’03, pp. 1398-1402, 2003.
information fidelity criterion (IFC) index
Ref：H.R. Sheikh, A.C. Bovik, and G. de Veciana, “An information fidelitycriterion for image quality assessment using natural scene statistics,” IEEETrans. IP, vol. 14, pp. 2117-2128, 2005.
visual information fidelity (VIF) index
Ref：H.R. Sheikh and A.C. Bovik, “Image information and visual quality,”IEEE Trans. IP, vol. 15, pp. 430-444, 2006.
visual signal to noise ratio (VSNR) index
Ref：D.M. Chandler and S.S. Hemami, “VSNR: a wavelet-based visualsignal-to-noise ratio for natural images,” IEEE Trans. IP, vol. 16, pp.2284-2298, 2007.
information content weighted SSIM (IW-SSIM) index
Ref：Z. Wang and Q. Li, “Information content weighting for perceptualimage quality assessment,” IEEE Trans. IP, vol. 20,
pp. 1185-1198, 2011.
Riesz transforms based feature similarity (RFSIM) index
Ref：L. Zhang, L. Zhang, and X. Mou, “RFSIM: a feature based imagequality assessment metric using Riesz transforms,” ICIP’10, pp. 321-324, 2010.
feature similarity (FSIM) index
Ref：L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM: a feature similarityindex for image quality assessment,” IEEE Trans. IP, vol. 20, pp. 2378-2386,2011.

All of the method above comes from ——
A COMPREHENSIVEEVALUATION OF FULL REFERENCE IMAGE QUALITY ASSESSMENT ALGORITHMS

http://blog.csdn.net/leixiaohua1020/article/details/38324973
http://blog.csdn.net/leixiaohua1020/article/details/12858773