ref: 29c46b64a2e0064beeba3ba200af2647ea1411b9
dir: /vp8/encoder/ssim.c/
/*
* 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
// Google version of SSIM
// SSIM
#define KERNEL 3
#define KERNEL_SIZE (2 * KERNEL + 1)
typedef unsigned char uint8;
typedef unsigned int uint32;
static const int K[KERNEL_SIZE] =
{
1, 4, 11, 16, 11, 4, 1 // 16 * exp(-0.3 * i * i)
};
static const double ki_w = 1. / 2304.; // 1 / sum(i:0..6, j..6) K[i]*K[j]
double get_ssimg(const uint8 *org, const uint8 *rec,
int xo, int yo, int W, int H,
const int stride1, const int stride2
)
{
// TODO(skal): use summed tables
int y, x;
const int ymin = (yo - KERNEL < 0) ? 0 : yo - KERNEL;
const int ymax = (yo + KERNEL > H - 1) ? H - 1 : yo + KERNEL;
const int xmin = (xo - KERNEL < 0) ? 0 : xo - KERNEL;
const int xmax = (xo + KERNEL > W - 1) ? W - 1 : xo + KERNEL;
// worst case of accumulation is a weight of 48 = 16 + 2 * (11 + 4 + 1)
// with a diff of 255, squares. That would a max error of 0x8ee0900,
// which fits into 32 bits integers.
uint32 w = 0, xm = 0, ym = 0, xxm = 0, xym = 0, yym = 0;
org += ymin * stride1;
rec += ymin * stride2;
for (y = ymin; y <= ymax; ++y, org += stride1, rec += stride2)
{
const int Wy = K[KERNEL + y - yo];
for (x = xmin; x <= xmax; ++x)
{
const int Wxy = Wy * K[KERNEL + x - xo];
// TODO(skal): inlined assembly
w += Wxy;
xm += Wxy * org[x];
ym += Wxy * rec[x];
xxm += Wxy * org[x] * org[x];
xym += Wxy * org[x] * rec[x];
yym += Wxy * rec[x] * rec[x];
}
}
{
const double iw = 1. / w;
const double iwx = xm * iw;
const double iwy = ym * iw;
double sxx = xxm * iw - iwx * iwx;
double syy = yym * iw - iwy * iwy;
// small errors are possible, due to rounding. Clamp to zero.
if (sxx < 0.) sxx = 0.;
if (syy < 0.) syy = 0.;
{
const double sxsy = sqrt(sxx * syy);
const double sxy = xym * iw - iwx * iwy;
static const double C11 = (0.01 * 0.01) * (255 * 255);
static const double C22 = (0.03 * 0.03) * (255 * 255);
static const double C33 = (0.015 * 0.015) * (255 * 255);
const double l = (2. * iwx * iwy + C11) / (iwx * iwx + iwy * iwy + C11);
const double c = (2. * sxsy + C22) / (sxx + syy + C22);
const double s = (sxy + C33) / (sxsy + C33);
return l * c * s;
}
}
}
double get_ssimfull_kernelg(const uint8 *org, const uint8 *rec,
int xo, int yo, int W, int H,
const int stride1, const int stride2)
{
// TODO(skal): use summed tables
// worst case of accumulation is a weight of 48 = 16 + 2 * (11 + 4 + 1)
// with a diff of 255, squares. That would a max error of 0x8ee0900,
// which fits into 32 bits integers.
int y_, x_;
uint32 xm = 0, ym = 0, xxm = 0, xym = 0, yym = 0;
org += (yo - KERNEL) * stride1;
org += (xo - KERNEL);
rec += (yo - KERNEL) * stride2;
rec += (xo - KERNEL);
for (y_ = 0; y_ < KERNEL_SIZE; ++y_, org += stride1, rec += stride2)
{
const int Wy = K[y_];
for (x_ = 0; x_ < KERNEL_SIZE; ++x_)
{
const int Wxy = Wy * K[x_];
// TODO(skal): inlined assembly
const int org_x = org[x_];
const int rec_x = rec[x_];
xm += Wxy * org_x;
ym += Wxy * rec_x;
xxm += Wxy * org_x * org_x;
xym += Wxy * org_x * rec_x;
yym += Wxy * rec_x * rec_x;
}
}
{
const double iw = ki_w;
const double iwx = xm * iw;
const double iwy = ym * iw;
double sxx = xxm * iw - iwx * iwx;
double syy = yym * iw - iwy * iwy;
// small errors are possible, due to rounding. Clamp to zero.
if (sxx < 0.) sxx = 0.;
if (syy < 0.) syy = 0.;
{
const double sxsy = sqrt(sxx * syy);
const double sxy = xym * iw - iwx * iwy;
static const double C11 = (0.01 * 0.01) * (255 * 255);
static const double C22 = (0.03 * 0.03) * (255 * 255);
static const double C33 = (0.015 * 0.015) * (255 * 255);
const double l = (2. * iwx * iwy + C11) / (iwx * iwx + iwy * iwy + C11);
const double c = (2. * sxsy + C22) / (sxx + syy + C22);
const double s = (sxy + C33) / (sxsy + C33);
return l * c * s;
}
}
}
double calc_ssimg(const uint8 *org, const uint8 *rec,
const int image_width, const int image_height,
const int stride1, const int stride2
)
{
int j, i;
double SSIM = 0.;
for (j = 0; j < KERNEL; ++j)
{
for (i = 0; i < image_width; ++i)
{
SSIM += get_ssimg(org, rec, i, j, image_width, image_height, stride1, stride2);
}
}
for (j = KERNEL; j < image_height - KERNEL; ++j)
{
for (i = 0; i < KERNEL; ++i)
{
SSIM += get_ssimg(org, rec, i, j, image_width, image_height, stride1, stride2);
}
for (i = KERNEL; i < image_width - KERNEL; ++i)
{
SSIM += get_ssimfull_kernelg(org, rec, i, j,
image_width, image_height, stride1, stride2);
}
for (i = image_width - KERNEL; i < image_width; ++i)
{
SSIM += get_ssimg(org, rec, i, j, image_width, image_height, stride1, stride2);
}
}
for (j = image_height - KERNEL; j < image_height; ++j)
{
for (i = 0; i < image_width; ++i)
{
SSIM += get_ssimg(org, rec, i, j, image_width, image_height, stride1, stride2);
}
}
return SSIM;
}
double vp8_calc_ssimg
(
YV12_BUFFER_CONFIG *source,
YV12_BUFFER_CONFIG *dest,
double *ssim_y,
double *ssim_u,
double *ssim_v
)
{
double ssim_all = 0;
int ysize = source->y_width * source->y_height;
int uvsize = ysize / 4;
*ssim_y = calc_ssimg(source->y_buffer, dest->y_buffer,
source->y_width, source->y_height,
source->y_stride, dest->y_stride);
*ssim_u = calc_ssimg(source->u_buffer, dest->u_buffer,
source->uv_width, source->uv_height,
source->uv_stride, dest->uv_stride);
*ssim_v = calc_ssimg(source->v_buffer, dest->v_buffer,
source->uv_width, source->uv_height,
source->uv_stride, dest->uv_stride);
ssim_all = (*ssim_y + *ssim_u + *ssim_v) / (ysize + uvsize + uvsize);
*ssim_y /= ysize;
*ssim_u /= uvsize;
*ssim_v /= uvsize;
return ssim_all;
}
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 long long c1 = 426148; // (256^2*(.01*255)^2
const static long long c2 = 3835331; //(256^2*(.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
)
{
long long ssim_n = (2*sum_s*sum_r+ c1)*(2*count*sum_sxr-2*sum_s*sum_r+c2);
long long ssim_d = (sum_s*sum_s +sum_r*sum_r+c1)*
(count*sum_sq_s-sum_s*sum_s + count*sum_sq_r-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;
double ssim3;
long long ssim_n;
long long ssim_d;
rtcd->ssimpf(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, &sum_sxr);
ssim_n = (2*sum_s*sum_r+ c1)*(2*256*sum_sxr-2*sum_s*sum_r+c2);
ssim_d = (sum_s*sum_s +sum_r*sum_r+c1)*
(256*sum_sq_s-sum_s*sum_s + 256*sum_sq_r-sum_r*sum_r +c2) ;
ssim3 = 256 * (ssim_d-ssim_n) / ssim_d;
return (long)( 256*ssim3 * ssim3 );
}
// TODO: (jbb) this 8x8 window might be too big + we may want to pick pixels
// such that the window regions 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;
double ssim_total=0;
// we can sample points as frequently as we like start with 1 per 8x8
for(i=0; i < height; i+=8, img1 += stride_img1*8, img2 += stride_img2*8)
{
for(j=0; j < width; j+=8 )
{
ssim_total += ssim_8x8(img1, stride_img1, img2, stride_img2, rtcd);
}
}
ssim_total /= (width/8 * height /8);
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;
//IF_RTCD(&cpi->rtcd.variance)
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;
}