blob: d0f8e490a4512c28799a4b31dad9df0cd58845da [file] [log] [blame]
/*
* 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 "onyx_int.h"
void vp8_ssim_parms_16x16_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 vp8_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;
SSIMPF_INVOKE(rtcd,16x16)(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;
SSIMPF_INVOKE(rtcd,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;
SSIMPF_INVOKE(rtcd,16x16)(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;
}