Commit ee87e20d authored by Jim Bankoski's avatar Jim Bankoski

Adds a new temporal consistency metric to libvpx.

Change-Id: Id61699ebf57ae4f8af96a468740c852b2f45f8e1
parent 2e36149c
/*
* Copyright (c) 2012 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 <string.h>
#include <limits.h>
#include <stdio.h>
#include "./vpx_config.h"
#if CONFIG_VP9_ENCODER
#include "./vp9_rtcd.h"
#endif
#include "test/acm_random.h"
#include "test/clear_system_state.h"
#include "test/register_state_check.h"
#include "test/util.h"
#include "third_party/googletest/src/include/gtest/gtest.h"
#include "vp9/encoder/vp9_ssim.h"
#include "vpx_mem/vpx_mem.h"
extern "C"
double vp9_get_ssim_metrics(uint8_t *img1, int img1_pitch,
uint8_t *img2, int img2_pitch,
int width, int height,
Ssimv *sv2, Metrics *m,
int do_inconsistency);
using libvpx_test::ACMRandom;
namespace {
class ConsistencyTestBase : public ::testing::Test {
public:
ConsistencyTestBase(int width, int height) : width_(width), height_(height) {}
static void SetUpTestCase() {
source_data_[0] = reinterpret_cast<uint8_t*>(
vpx_memalign(kDataAlignment, kDataBufferSize));
reference_data_[0] = reinterpret_cast<uint8_t*>(
vpx_memalign(kDataAlignment, kDataBufferSize));
source_data_[1] = reinterpret_cast<uint8_t*>(
vpx_memalign(kDataAlignment, kDataBufferSize));
reference_data_[1] = reinterpret_cast<uint8_t*>(
vpx_memalign(kDataAlignment, kDataBufferSize));
ssim_array_ = new Ssimv[kDataBufferSize / 16];
}
static void ClearSsim() {
memset(ssim_array_, 0, kDataBufferSize / 16);
}
static void TearDownTestCase() {
vpx_free(source_data_[0]);
source_data_[0] = NULL;
vpx_free(reference_data_[0]);
reference_data_[0] = NULL;
vpx_free(source_data_[1]);
source_data_[1] = NULL;
vpx_free(reference_data_[1]);
reference_data_[1] = NULL;
delete ssim_array_;
}
virtual void TearDown() {
libvpx_test::ClearSystemState();
}
protected:
// Handle frames up to 640x480
static const int kDataAlignment = 16;
static const int kDataBufferSize = 640*480;
virtual void SetUp() {
source_stride_ = (width_ + 31) & ~31;
reference_stride_ = width_ * 2;
rnd_.Reset(ACMRandom::DeterministicSeed());
}
void FillRandom(uint8_t *data, int stride, int width, int height) {
for (int h = 0; h < height; ++h) {
for (int w = 0; w < width; ++w) {
data[h * stride + w] = rnd_.Rand8();
}
}
}
void FillRandom(uint8_t *data, int stride) {
FillRandom(data, stride, width_, height_);
}
void Copy(uint8_t *reference, uint8_t *source) {
memcpy(reference, source, kDataBufferSize);
}
void Blur(uint8_t *data, int stride, int taps) {
int sum = 0;
int half_taps = taps / 2;
for (int h = 0; h < height_; ++h) {
for (int w = 0; w < taps; ++w) {
sum += data[w + h * stride];
}
for (int w = taps; w < width_; ++w) {
sum += data[w + h * stride] - data[w - taps + h * stride];
data[w - half_taps + h * stride] = (sum + half_taps) / taps;
}
}
for (int w = 0; w < width_; ++w) {
for (int h = 0; h < taps; ++h) {
sum += data[h + w * stride];
}
for (int h = taps; h < height_; ++h) {
sum += data[w + h * stride] - data[(h - taps) * stride + w];
data[(h - half_taps) * stride + w] = (sum + half_taps) / taps;
}
}
}
int width_, height_;
static uint8_t* source_data_[2];
int source_stride_;
static uint8_t* reference_data_[2];
int reference_stride_;
static Ssimv *ssim_array_;
Metrics metrics_;
ACMRandom rnd_;
};
#if CONFIG_VP9_ENCODER
typedef std::tr1::tuple<int, int> ConsistencyParam;
class ConsistencyVP9Test
: public ConsistencyTestBase,
public ::testing::WithParamInterface<ConsistencyParam> {
public:
ConsistencyVP9Test() : ConsistencyTestBase(GET_PARAM(0), GET_PARAM(1)) {}
protected:
double CheckConsistency(int frame) {
EXPECT_LT(frame, 2)<< "Frame to check has to be less than 2.";
return
vp9_get_ssim_metrics(source_data_[frame], source_stride_,
reference_data_[frame], reference_stride_,
width_, height_, ssim_array_, &metrics_, 1);
}
};
#endif // CONFIG_VP9_ENCODER
uint8_t* ConsistencyTestBase::source_data_[2] = {NULL, NULL};
uint8_t* ConsistencyTestBase::reference_data_[2] = {NULL, NULL};
Ssimv* ConsistencyTestBase::ssim_array_ = NULL;
#if CONFIG_VP9_ENCODER
TEST_P(ConsistencyVP9Test, ConsistencyIsZero) {
FillRandom(source_data_[0], source_stride_);
Copy(source_data_[1], source_data_[0]);
Copy(reference_data_[0], source_data_[0]);
Blur(reference_data_[0], reference_stride_, 3);
Copy(reference_data_[1], source_data_[0]);
Blur(reference_data_[1], reference_stride_, 3);
double inconsistency = CheckConsistency(1);
inconsistency = CheckConsistency(0);
EXPECT_EQ(inconsistency, 0.0)
<< "Should have 0 inconsistency if they are exactly the same.";
// If sources are not consistent reference frames inconsistency should
// be less than if the source is consistent.
FillRandom(source_data_[0], source_stride_);
FillRandom(source_data_[1], source_stride_);
FillRandom(reference_data_[0], reference_stride_);
FillRandom(reference_data_[1], reference_stride_);
CheckConsistency(0);
inconsistency = CheckConsistency(1);
Copy(source_data_[1], source_data_[0]);
CheckConsistency(0);
double inconsistency2 = CheckConsistency(1);
EXPECT_LT(inconsistency, inconsistency2)
<< "Should have less inconsistency if source itself is inconsistent.";
// Less of a blur should be less inconsistent than more blur coming off a
// a frame with no blur.
ClearSsim();
FillRandom(source_data_[0], source_stride_);
Copy(source_data_[1], source_data_[0]);
Copy(reference_data_[0], source_data_[0]);
Copy(reference_data_[1], source_data_[0]);
Blur(reference_data_[1], reference_stride_, 4);
CheckConsistency(0);
inconsistency = CheckConsistency(1);
ClearSsim();
Copy(reference_data_[1], source_data_[0]);
Blur(reference_data_[1], reference_stride_, 8);
CheckConsistency(0);
inconsistency2 = CheckConsistency(1);
EXPECT_LT(inconsistency, inconsistency2)
<< "Stronger Blur should produce more inconsistency.";
}
#endif // CONFIG_VP9_ENCODER
using std::tr1::make_tuple;
//------------------------------------------------------------------------------
// C functions
#if CONFIG_VP9_ENCODER
const ConsistencyParam c_vp9_tests[] = {
make_tuple(320, 240),
make_tuple(318, 242),
make_tuple(318, 238),
};
INSTANTIATE_TEST_CASE_P(C, ConsistencyVP9Test,
::testing::ValuesIn(c_vp9_tests));
#endif
} // namespace
......@@ -151,6 +151,8 @@ LIBVPX_TEST_SRCS-$(CONFIG_VP9) += vp9_intrapred_test.cc
ifeq ($(CONFIG_VP9_ENCODER),yes)
LIBVPX_TEST_SRCS-$(CONFIG_SPATIAL_SVC) += svc_test.cc
LIBVPX_TEST_SRCS-$(CONFIG_INTERNAL_STATS) += blockiness_test.cc
LIBVPX_TEST_SRCS-$(CONFIG_INTERNAL_STATS) += consistency_test.cc
endif
ifeq ($(CONFIG_VP9_ENCODER)$(CONFIG_VP9_TEMPORAL_DENOISING),yesyes)
......
......@@ -1618,7 +1618,8 @@ VP9_COMP *vp9_create_compressor(VP9EncoderConfig *oxcf,
#if CONFIG_INTERNAL_STATS
cpi->b_calculate_ssimg = 0;
cpi->b_calculate_blockiness = 1;
cpi->b_calculate_consistency = 1;
cpi->total_inconsistency = 0;
cpi->count = 0;
cpi->bytes = 0;
......@@ -1669,6 +1670,10 @@ VP9_COMP *vp9_create_compressor(VP9EncoderConfig *oxcf,
cpi->total_blockiness = 0;
}
if (cpi->b_calculate_consistency) {
cpi->ssim_vars = vpx_malloc(sizeof(*cpi->ssim_vars)*720*480);
}
#endif
cpi->first_time_stamp_ever = INT64_MAX;
......@@ -1865,6 +1870,12 @@ VP9_COMP *vp9_create_compressor(VP9EncoderConfig *oxcf,
return cpi;
}
#define SNPRINT(H, T) \
snprintf((H) + strlen(H), sizeof(H) - strlen(H), (T))
#define SNPRINT2(H, T, V) \
snprintf((H) + strlen(H), sizeof(H) - strlen(H), (T), (V))
void vp9_remove_compressor(VP9_COMP *cpi) {
VP9_COMMON *const cm = &cpi->common;
......@@ -1878,8 +1889,9 @@ void vp9_remove_compressor(VP9_COMP *cpi) {
#if CONFIG_INTERNAL_STATS
vp9_clear_system_state();
// printf("\n8x8-4x4:%d-%d\n", cpi->t8x8_count, cpi->t4x4_count);
if (cpi->oxcf.pass != 1) {
char headings[512] = {0};
char results[512] = {0};
FILE *f = fopen("opsnr.stt", "a");
double time_encoded = (cpi->last_end_time_stamp_seen
- cpi->first_time_stamp_ever) / 10000000.000;
......@@ -1897,39 +1909,39 @@ void vp9_remove_compressor(VP9_COMP *cpi) {
vpx_sse_to_psnr((double)cpi->totalp_samples, peak,
(double)cpi->totalp_sq_error);
const double total_ssim = 100 * pow(cpi->summed_quality /
cpi->summed_weights, 8.0);
cpi->summed_weights, 8.0);
snprintf(headings, sizeof(headings),
"Bitrate\tAVGPsnr\tGLBPsnr\tAVPsnrP\tGLPsnrP\t"
"VPXSSIM\tFASTSIM\tPSNRHVS");
snprintf(results, sizeof(results),
"%7.2f\t%7.3f\t%7.3f\t%7.3f\t%7.3f\t"
"%7.3f\t%7.3f\t%7.3f", dr,
cpi->total / cpi->count, total_psnr,
cpi->totalp / cpi->count, totalp_psnr, total_ssim,
cpi->total_fastssim_all / cpi->count,
cpi->total_psnrhvs_all / cpi->count);
if (cpi->b_calculate_blockiness) {
fprintf(f, "Bitrate\tAVGPsnr\tGLBPsnr\tAVPsnrP\tGLPsnrP\t"
"VPXSSIM\tVPSSIMP\tFASTSSIM\tPSNRHVS\tTime(ms)\n");
fprintf(f, "%7.2f\t%7.3f\t%7.3f\t%7.3f\t%7.3f\t%7.3f\t"
"%7.3f\t%7.3f\t%8.0f\n",
dr, cpi->total / cpi->count, total_psnr,
cpi->totalp / cpi->count, totalp_psnr, total_ssim,
cpi->total_fastssim_all / cpi->count,
cpi->total_psnrhvs_all / cpi->count,
total_encode_time);
} else {
fprintf(f, "Bitrate\tAVGPsnr\tGLBPsnr\tAVPsnrP\tGLPsnrP\t"
"VPXSSIM\tVPSSIMP\tBlockiness\tFASTSSIM\tPSNRHVS\tTime(ms)\n");
fprintf(f, "%7.2f\t%7.3f\t%7.3f\t%7.3f\t%7.3f\t%7.3f\t"
"%7.3f\t%7.3f\t%7.3f\t%8.0f\n",
dr, cpi->total / cpi->count, total_psnr,
cpi->totalp / cpi->count, totalp_psnr, total_ssim,
cpi->total_blockiness / cpi->count,
cpi->total_fastssim_all / cpi->count,
cpi->total_psnrhvs_all / cpi->count,
total_encode_time);
SNPRINT(headings, "\t Block");
SNPRINT2(results, "\t%7.3f", cpi->total_blockiness / cpi->count);
}
}
if (cpi->b_calculate_consistency) {
double consistency =
vpx_sse_to_psnr((double)cpi->totalp_samples, peak,
(double)cpi->total_inconsistency);
if (cpi->b_calculate_ssimg) {
fprintf(f, "BitRate\tSSIM_Y\tSSIM_U\tSSIM_V\tSSIM_A\t Time(ms)\n");
fprintf(f, "%7.2f\t%6.4f\t%6.4f\t%6.4f\t%6.4f\t%8.0f\n", dr,
cpi->total_ssimg_y / cpi->count,
cpi->total_ssimg_u / cpi->count,
cpi->total_ssimg_v / cpi->count,
cpi->total_ssimg_all / cpi->count, total_encode_time);
SNPRINT(headings, "\tConsist");
SNPRINT2(results, "\t%7.3f", consistency);
}
if (cpi->b_calculate_ssimg) {
SNPRINT(headings, "\t SSIMG");
SNPRINT2(results, "\t%7.3f", cpi->total_ssimg_all / cpi->count);
}
fprintf(f, "%s\t Time\n", headings);
fprintf(f, "%s\t%8.0f\n", results, total_encode_time);
}
fclose(f);
......@@ -4201,6 +4213,16 @@ int vp9_get_compressed_data(VP9_COMP *cpi, unsigned int *frame_flags,
cm->frame_to_show->y_stride,
cpi->Source->y_width, cpi->Source->y_height);
if (cpi->b_calculate_consistency)
cpi->total_inconsistency += vp9_get_ssim_metrics(cpi->Source->y_buffer,
cpi->Source->y_stride,
cm->frame_to_show->y_buffer,
cm->frame_to_show->y_stride,
cpi->Source->y_width,
cpi->Source->y_height,
cpi->ssim_vars,
&cpi->metrics, 1);
if (cpi->b_calculate_ssimg) {
double y, u, v, frame_all;
#if CONFIG_VP9_HIGHBITDEPTH
......
......@@ -34,6 +34,9 @@
#include "vp9/encoder/vp9_quantize.h"
#include "vp9/encoder/vp9_ratectrl.h"
#include "vp9/encoder/vp9_rd.h"
#if CONFIG_INTERNAL_STATS
#include "vp9/encoder/vp9_ssim.h"
#endif
#include "vp9/encoder/vp9_speed_features.h"
#include "vp9/encoder/vp9_svc_layercontext.h"
#include "vp9/encoder/vp9_tokenize.h"
......@@ -429,6 +432,10 @@ typedef struct VP9_COMP {
int b_calculate_ssimg;
int b_calculate_blockiness;
int b_calculate_consistency;
double total_inconsistency;
Ssimv *ssim_vars;
Metrics metrics;
#endif
int b_calculate_psnr;
......
......@@ -8,8 +8,8 @@
* be found in the AUTHORS file in the root of the source tree.
*/
#include <math.h>
#include "./vp9_rtcd.h"
#include "vp9/encoder/vp9_ssim.h"
void vp9_ssim_parms_16x16_c(uint8_t *s, int sp, uint8_t *r,
......@@ -201,6 +201,251 @@ double vp9_calc_ssimg(YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest,
return ssim_all;
}
// traditional ssim as per: http://en.wikipedia.org/wiki/Structural_similarity
//
// Re working out the math ->
//
// ssim(x,y) = (2*mean(x)*mean(y) + c1)*(2*cov(x,y)+c2) /
// ((mean(x)^2+mean(y)^2+c1)*(var(x)+var(y)+c2))
//
// mean(x) = sum(x) / n
//
// cov(x,y) = (n*sum(xi*yi)-sum(x)*sum(y))/(n*n)
//
// var(x) = (n*sum(xi*xi)-sum(xi)*sum(xi))/(n*n)
//
// ssim(x,y) =
// (2*sum(x)*sum(y)/(n*n) + c1)*(2*(n*sum(xi*yi)-sum(x)*sum(y))/(n*n)+c2) /
// (((sum(x)*sum(x)+sum(y)*sum(y))/(n*n) +c1) *
// ((n*sum(xi*xi) - sum(xi)*sum(xi))/(n*n)+
// (n*sum(yi*yi) - sum(yi)*sum(yi))/(n*n)+c2)))
//
// factoring out n*n
//
// ssim(x,y) =
// (2*sum(x)*sum(y) + n*n*c1)*(2*(n*sum(xi*yi)-sum(x)*sum(y))+n*n*c2) /
// (((sum(x)*sum(x)+sum(y)*sum(y)) + n*n*c1) *
// (n*sum(xi*xi)-sum(xi)*sum(xi)+n*sum(yi*yi)-sum(yi)*sum(yi)+n*n*c2))
//
// Replace c1 with n*n * c1 for the final step that leads to this code:
// The final step scales by 12 bits so we don't lose precision in the constants.
double ssimv_similarity(Ssimv *sv, int64_t n) {
// Scale the constants by number of pixels.
const int64_t c1 = (cc1 * n * n) >> 12;
const int64_t c2 = (cc2 * n * n) >> 12;
const double l = 1.0 * (2 * sv->sum_s * sv->sum_r + c1) /
(sv->sum_s * sv->sum_s + sv->sum_r * sv->sum_r + c1);
// Since these variables are unsigned sums, convert to double so
// math is done in double arithmetic.
const double v = (2.0 * n * sv->sum_sxr - 2 * sv->sum_s * sv->sum_r + c2)
/ (n * sv->sum_sq_s - sv->sum_s * sv->sum_s + n * sv->sum_sq_r
- sv->sum_r * sv->sum_r + c2);
return l * v;
}
// The first term of the ssim metric is a luminance factor.
//
// (2*mean(x)*mean(y) + c1)/ (mean(x)^2+mean(y)^2+c1)
//
// This luminance factor is super sensitive to the dark side of luminance
// values and completely insensitive on the white side. check out 2 sets
// (1,3) and (250,252) the term gives ( 2*1*3/(1+9) = .60
// 2*250*252/ (250^2+252^2) => .99999997
//
// As a result in this tweaked version of the calculation in which the
// luminance is taken as percentage off from peak possible.
//
// 255 * 255 - (sum_s - sum_r) / count * (sum_s - sum_r) / count
//
double ssimv_similarity2(Ssimv *sv, int64_t n) {
// Scale the constants by number of pixels.
const int64_t c1 = (cc1 * n * n) >> 12;
const int64_t c2 = (cc2 * n * n) >> 12;
const double mean_diff = (1.0 * sv->sum_s - sv->sum_r) / n;
const double l = (255 * 255 - mean_diff * mean_diff + c1) / (255 * 255 + c1);
// Since these variables are unsigned, sums convert to double so
// math is done in double arithmetic.
const double v = (2.0 * n * sv->sum_sxr - 2 * sv->sum_s * sv->sum_r + c2)
/ (n * sv->sum_sq_s - sv->sum_s * sv->sum_s +
n * sv->sum_sq_r - sv->sum_r * sv->sum_r + c2);
return l * v;
}
void ssimv_parms(uint8_t *img1, int img1_pitch, uint8_t *img2, int img2_pitch,
Ssimv *sv) {
vp9_ssim_parms_8x8(img1, img1_pitch, img2, img2_pitch,
&sv->sum_s, &sv->sum_r, &sv->sum_sq_s, &sv->sum_sq_r,
&sv->sum_sxr);
}
double vp9_get_ssim_metrics(uint8_t *img1, int img1_pitch,
uint8_t *img2, int img2_pitch,
int width, int height,
Ssimv *sv2, Metrics *m,
int do_inconsistency) {
double dssim_total = 0;
double ssim_total = 0;
double ssim2_total = 0;
double inconsistency_total = 0;
int i, j;
int c = 0;
double norm;
double old_ssim_total = 0;
vp9_clear_system_state();
// We can sample points as frequently as we like start with 1 per 4x4.
for (i = 0; i < height; i += 4,
img1 += img1_pitch * 4, img2 += img2_pitch * 4) {
for (j = 0; j < width; j += 4, ++c) {
Ssimv sv = {0};
double ssim;
double ssim2;
double dssim;
uint32_t var_new;
uint32_t var_old;
uint32_t mean_new;
uint32_t mean_old;
double ssim_new;
double ssim_old;
// Not sure there's a great way to handle the edge pixels
// in ssim when using a window. Seems biased against edge pixels
// however you handle this. This uses only samples that are
// fully in the frame.
if (j + 8 <= width && i + 8 <= height) {
ssimv_parms(img1 + j, img1_pitch, img2 + j, img2_pitch, &sv);
}
ssim = ssimv_similarity(&sv, 64);
ssim2 = ssimv_similarity2(&sv, 64);
sv.ssim = ssim2;
// dssim is calculated to use as an actual error metric and
// is scaled up to the same range as sum square error.
// Since we are subsampling every 16th point maybe this should be
// *16 ?
dssim = 255 * 255 * (1 - ssim2) / 2;
// Here I introduce a new error metric: consistency-weighted
// SSIM-inconsistency. This metric isolates frames where the
// SSIM 'suddenly' changes, e.g. if one frame in every 8 is much
// sharper or blurrier than the others. Higher values indicate a
// temporally inconsistent SSIM. There are two ideas at work:
//
// 1) 'SSIM-inconsistency': the total inconsistency value
// reflects how much SSIM values are changing between this
// source / reference frame pair and the previous pair.
//
// 2) 'consistency-weighted': weights de-emphasize areas in the
// frame where the scene content has changed. Changes in scene
// content are detected via changes in local variance and local
// mean.
//
// Thus the overall measure reflects how inconsistent the SSIM
// values are, over consistent regions of the frame.
//
// The metric has three terms:
//
// term 1 -> uses change in scene Variance to weight error score
// 2 * var(Fi)*var(Fi-1) / (var(Fi)^2+var(Fi-1)^2)
// larger changes from one frame to the next mean we care
// less about consistency.
//
// term 2 -> uses change in local scene luminance to weight error
// 2 * avg(Fi)*avg(Fi-1) / (avg(Fi)^2+avg(Fi-1)^2)
// larger changes from one frame to the next mean we care
// less about consistency.
//
// term3 -> measures inconsistency in ssim scores between frames
// 1 - ( 2 * ssim(Fi)*ssim(Fi-1)/(ssim(Fi)^2+sssim(Fi-1)^2).
//
// This term compares the ssim score for the same location in 2
// subsequent frames.
var_new = sv.sum_sq_s - sv.sum_s * sv.sum_s / 64;
var_old = sv2[c].sum_sq_s - sv2[c].sum_s * sv2[c].sum_s / 64;
mean_new = sv.sum_s;
mean_old = sv2[c].sum_s;
ssim_new = sv.ssim;
ssim_old = sv2[c].ssim;
if (do_inconsistency) {
// We do the metric once for every 4x4 block in the image. Since
// we are scaling the error to SSE for use in a psnr calculation
// 1.0 = 4x4x255x255 the worst error we can possibly have.
static const double kScaling = 4. * 4 * 255 * 255;
// The constants have to be non 0 to avoid potential divide by 0
// issues other than that they affect kind of a weighting between
// the terms. No testing of what the right terms should be has been
// done.
static const double c1 = 1, c2 = 1, c3 = 1;
// This measures how much consistent variance is in two consecutive
// source frames. 1.0 means they have exactly the same variance.
const double variance_term = (2.0 * var_old * var_new + c1) /
(1.0 * var_old * var_old + 1.0 * var_new * var_new + c1);
// This measures how consistent the local mean are between two
// consecutive frames. 1.0 means they have exactly the same mean.
const double mean_term = (2.0 * mean_old * mean_new + c2) /
(1.0 * mean_old * mean_old + 1.0 * mean_new * mean_new + c2);
// This measures how consistent the ssims of two
// consecutive frames is. 1.0 means they are exactly the same.
double ssim_term = pow((2.0 * ssim_old * ssim_new + c3) /
(ssim_old * ssim_old + ssim_new * ssim_new + c3),
5);
double this_inconsistency;
// Floating point math sometimes makes this > 1 by a tiny bit.
// We want the metric to scale between 0 and 1.0 so we can convert
// it to an snr scaled value.
if (ssim_term > 1)
ssim_term = 1;
// This converts the consistency metric to an inconsistency metric
// ( so we can scale it like psnr to something like sum square error.
// The reason for the variance and mean terms is the assumption that
// if there are big changes in the source we shouldn't penalize
// inconsistency in ssim scores a bit less as it will be less visible
// to the user.
this_inconsistency = (1 - ssim_term) * variance_term * mean_term;
this_inconsistency *= kScaling;
inconsistency_total += this_inconsistency;
}
sv2[c] = sv;
ssim_total += ssim;
ssim2_total += ssim2;
dssim_total += dssim;
old_ssim_total += ssim_old;
}
old_ssim_total += 0;
}
norm = 1. / (width / 4) / (height / 4);
ssim_total *= norm;
ssim2_total *= norm;
m->ssim2 = ssim2_total;
m->ssim = ssim_total;
if (old_ssim_total == 0)
inconsistency_total = 0;
m->ssimc = inconsistency_total;
m->dssim = dssim_total;
return inconsistency_total;
}
#if CONFIG_VP9_HIGHBITDEPTH
double vp9_highbd_calc_ssim(YV12_BUFFER_CONFIG *source,
YV12_BUFFER_CONFIG *dest,
......
......@@ -17,6 +17,52 @@ extern "C" {
#include "vpx_scale/yv12config.h"
// metrics used for calculating ssim, ssim2, dssim, and ssimc
typedef struct {
// source sum ( over 8x8 region )
uint64_t sum_s;
// reference sum (over 8x8 region )
uint64_t sum_r;
// source sum squared ( over 8x8 region )
uint64_t sum_sq_s;
// reference sum squared (over 8x8 region )
uint64_t sum_sq_r;
// sum of source times reference (over 8x8 region)
uint64_t sum_sxr;
// calculated ssim score between source and reference
double ssim;
} Ssimv;
// metrics collected on a frame basis
typedef struct {
// ssim consistency error metric ( see code for explanation )
double ssimc;
// standard ssim
double ssim;
// revised ssim ( see code for explanation)
double ssim2;
// ssim restated as an error metric like sse
double dssim;
// dssim converted to decibels
double dssimd;
// ssimc converted to decibels
double ssimcd;
} Metrics;
double vp9_get_ssim_metrics(uint8_t *img1, int img1_pitch, uint8_t *img2,
int img2_pitch, int width, int height, Ssimv *sv2,
Metrics *m, int do_inconsistency);
double vp9_calc_ssim(YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest,
double *weight);
......
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