/* * Copyright (c) 2010 The WebM project authors. All Rights Reserved. * * Use of this source code is governed by a BSD-style license * that can be found in the LICENSE file in the root of the source * tree. An additional intellectual property rights grant can be found * in the file PATENTS. All contributing project authors may * be found in the AUTHORS file in the root of the source tree. */ #include "vpx_scale/yv12config.h" #include "math.h" #include "onyx_int.h" #if CONFIG_RUNTIME_CPU_DETECT #define IF_RTCD(x) (x) #else #define IF_RTCD(x) NULL #endif void ssim_parms_c ( unsigned char *s, int sp, unsigned char *r, int rp, unsigned long *sum_s, unsigned long *sum_r, unsigned long *sum_sq_s, unsigned long *sum_sq_r, unsigned long *sum_sxr ) { int i,j; for(i=0;i<16;i++,s+=sp,r+=rp) { for(j=0;j<16;j++) { *sum_s += s[j]; *sum_r += r[j]; *sum_sq_s += s[j] * s[j]; *sum_sq_r += r[j] * r[j]; *sum_sxr += s[j] * r[j]; } } } void ssim_parms_8x8_c ( unsigned char *s, int sp, unsigned char *r, int rp, unsigned long *sum_s, unsigned long *sum_r, unsigned long *sum_sq_s, unsigned long *sum_sq_r, unsigned long *sum_sxr ) { int i,j; for(i=0;i<8;i++,s+=sp,r+=rp) { for(j=0;j<8;j++) { *sum_s += s[j]; *sum_r += r[j]; *sum_sq_s += s[j] * s[j]; *sum_sq_r += r[j] * r[j]; *sum_sxr += s[j] * r[j]; } } } const static int64_t cc1 = 26634; // (64^2*(.01*255)^2 const static int64_t cc2 = 239708; // (64^2*(.03*255)^2 static double similarity ( unsigned long sum_s, unsigned long sum_r, unsigned long sum_sq_s, unsigned long sum_sq_r, unsigned long sum_sxr, int count ) { int64_t ssim_n, ssim_d; int64_t c1, c2; //scale the constants by number of pixels c1 = (cc1*count*count)>>12; c2 = (cc2*count*count)>>12; ssim_n = (2*sum_s*sum_r+ c1)*((int64_t) 2*count*sum_sxr- (int64_t) 2*sum_s*sum_r+c2); ssim_d = (sum_s*sum_s +sum_r*sum_r+c1)* ((int64_t)count*sum_sq_s-(int64_t)sum_s*sum_s + (int64_t)count*sum_sq_r-(int64_t) sum_r*sum_r +c2) ; return ssim_n * 1.0 / ssim_d; } static double ssim_16x16(unsigned char *s,int sp, unsigned char *r,int rp, const vp8_variance_rtcd_vtable_t *rtcd) { unsigned long sum_s=0,sum_r=0,sum_sq_s=0,sum_sq_r=0,sum_sxr=0; rtcd->ssimpf(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, &sum_sxr); return similarity(sum_s, sum_r, sum_sq_s, sum_sq_r, sum_sxr, 256); } static double ssim_8x8(unsigned char *s,int sp, unsigned char *r,int rp, const vp8_variance_rtcd_vtable_t *rtcd) { unsigned long sum_s=0,sum_r=0,sum_sq_s=0,sum_sq_r=0,sum_sxr=0; rtcd->ssimpf_8x8(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, &sum_sxr); return similarity(sum_s, sum_r, sum_sq_s, sum_sq_r, sum_sxr, 64); } // TODO: (jbb) tried to scale this function such that we may be able to use it // for distortion metric in mode selection code ( provided we do a reconstruction) long dssim(unsigned char *s,int sp, unsigned char *r,int rp, const vp8_variance_rtcd_vtable_t *rtcd) { unsigned long sum_s=0,sum_r=0,sum_sq_s=0,sum_sq_r=0,sum_sxr=0; int64_t ssim3; int64_t ssim_n1,ssim_n2; int64_t ssim_d1,ssim_d2; int64_t ssim_t1,ssim_t2; int64_t c1, c2; // normalize by 256/64 c1 = cc1*16; c2 = cc2*16; rtcd->ssimpf(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, &sum_sxr); ssim_n1 = (2*sum_s*sum_r+ c1); ssim_n2 =((int64_t) 2*256*sum_sxr-(int64_t) 2*sum_s*sum_r+c2); ssim_d1 =((int64_t)sum_s*sum_s +(int64_t)sum_r*sum_r+c1); ssim_d2 = (256 * (int64_t) sum_sq_s-(int64_t) sum_s*sum_s + (int64_t) 256*sum_sq_r-(int64_t) sum_r*sum_r +c2) ; ssim_t1 = 256 - 256 * ssim_n1 / ssim_d1; ssim_t2 = 256 - 256 * ssim_n2 / ssim_d2; ssim3 = 256 *ssim_t1 * ssim_t2; if(ssim3 <0 ) ssim3=0; return (long)( ssim3 ); } // We are using a 8x8 moving window with starting location of each 8x8 window // on the 4x4 pixel grid. Such arrangement allows the windows to overlap // block boundaries to penalize blocking artifacts. double vp8_ssim2 ( unsigned char *img1, unsigned char *img2, int stride_img1, int stride_img2, int width, int height, const vp8_variance_rtcd_vtable_t *rtcd ) { int i,j; int samples =0; double ssim_total=0; // sample point start with each 4x4 location for(i=0; i < height-8; i+=4, img1 += stride_img1*4, img2 += stride_img2*4) { for(j=0; j < width-8; j+=4 ) { double v = ssim_8x8(img1+j, stride_img1, img2+j, stride_img2, rtcd); ssim_total += v; samples++; } } ssim_total /= samples; return ssim_total; } double vp8_calc_ssim ( YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest, int lumamask, double *weight, const vp8_variance_rtcd_vtable_t *rtcd ) { double a, b, c; double ssimv; a = vp8_ssim2(source->y_buffer, dest->y_buffer, source->y_stride, dest->y_stride, source->y_width, source->y_height, rtcd); b = vp8_ssim2(source->u_buffer, dest->u_buffer, source->uv_stride, dest->uv_stride, source->uv_width, source->uv_height, rtcd); c = vp8_ssim2(source->v_buffer, dest->v_buffer, source->uv_stride, dest->uv_stride, source->uv_width, source->uv_height, rtcd); ssimv = a * .8 + .1 * (b + c); *weight = 1; return ssimv; } double vp8_calc_ssimg ( YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest, double *ssim_y, double *ssim_u, double *ssim_v, const vp8_variance_rtcd_vtable_t *rtcd ) { double ssim_all = 0; double a, b, c; a = vp8_ssim2(source->y_buffer, dest->y_buffer, source->y_stride, dest->y_stride, source->y_width, source->y_height, rtcd); b = vp8_ssim2(source->u_buffer, dest->u_buffer, source->uv_stride, dest->uv_stride, source->uv_width, source->uv_height, rtcd); c = vp8_ssim2(source->v_buffer, dest->v_buffer, source->uv_stride, dest->uv_stride, source->uv_width, source->uv_height, rtcd); *ssim_y = a; *ssim_u = b; *ssim_v = c; ssim_all = (a * 4 + b + c) /6; return ssim_all; }