9757c1aded
PSNR HVS is a human visual system weighted version of SNR that's gained some popularity from academia and apparently better matches MOS testing. This code is borrowed from the Daala Project but uses our FDCT code. Change-Id: Idd10fbc93129f7f4734946f6009f87d0f44cd2d7
228 lines
10 KiB
C
228 lines
10 KiB
C
/*
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* Copyright (c) 2010 The WebM project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*
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* This code was originally written by: Gregory Maxwell, at the Daala
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* project.
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*/
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#include <stdio.h>
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#include <stdlib.h>
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#include <math.h>
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#include "./vpx_config.h"
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#include "./vp9_rtcd.h"
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#include "vp9/encoder/vp9_ssim.h"
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#if !defined(M_PI)
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# define M_PI (3.141592653589793238462643)
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#endif
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#include <string.h>
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typedef int16_t od_coeff;
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typedef int16_t tran_low_t;
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extern void vp9_fdct8x8_c(const int16_t *input, tran_low_t *output, int stride);
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void od_bin_fdct8x8(od_coeff *y, int ystride, const od_coeff *x, int xstride) {
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(void) xstride;
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vp9_fdct8x8_c(x, y, ystride);
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}
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/* Normalized inverse quantization matrix for 8x8 DCT at the point of
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* transparency. This is not the JPEG based matrix from the paper,
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this one gives a slightly higher MOS agreement.*/
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float csf_y[8][8] = {{1.6193873005, 2.2901594831, 2.08509755623, 1.48366094411,
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1.00227514334, 0.678296995242, 0.466224900598, 0.3265091542}, {2.2901594831,
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1.94321815382, 2.04793073064, 1.68731108984, 1.2305666963, 0.868920337363,
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0.61280991668, 0.436405793551}, {2.08509755623, 2.04793073064,
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1.34329019223, 1.09205635862, 0.875748795257, 0.670882927016,
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0.501731932449, 0.372504254596}, {1.48366094411, 1.68731108984,
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1.09205635862, 0.772819797575, 0.605636379554, 0.48309405692,
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0.380429446972, 0.295774038565}, {1.00227514334, 1.2305666963,
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0.875748795257, 0.605636379554, 0.448996256676, 0.352889268808,
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0.283006984131, 0.226951348204}, {0.678296995242, 0.868920337363,
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0.670882927016, 0.48309405692, 0.352889268808, 0.27032073436,
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0.215017739696, 0.17408067321}, {0.466224900598, 0.61280991668,
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0.501731932449, 0.380429446972, 0.283006984131, 0.215017739696,
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0.168869545842, 0.136153931001}, {0.3265091542, 0.436405793551,
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0.372504254596, 0.295774038565, 0.226951348204, 0.17408067321,
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0.136153931001, 0.109083846276}};
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float csf_cb420[8][8] = {
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{1.91113096927, 2.46074210438, 1.18284184739, 1.14982565193, 1.05017074788,
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0.898018824055, 0.74725392039, 0.615105596242}, {2.46074210438,
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1.58529308355, 1.21363250036, 1.38190029285, 1.33100189972,
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1.17428548929, 0.996404342439, 0.830890433625}, {1.18284184739,
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1.21363250036, 0.978712413627, 1.02624506078, 1.03145147362,
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0.960060382087, 0.849823426169, 0.731221236837}, {1.14982565193,
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1.38190029285, 1.02624506078, 0.861317501629, 0.801821139099,
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0.751437590932, 0.685398513368, 0.608694761374}, {1.05017074788,
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1.33100189972, 1.03145147362, 0.801821139099, 0.676555426187,
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0.605503172737, 0.55002013668, 0.495804539034}, {0.898018824055,
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1.17428548929, 0.960060382087, 0.751437590932, 0.605503172737,
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0.514674450957, 0.454353482512, 0.407050308965}, {0.74725392039,
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0.996404342439, 0.849823426169, 0.685398513368, 0.55002013668,
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0.454353482512, 0.389234902883, 0.342353999733}, {0.615105596242,
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0.830890433625, 0.731221236837, 0.608694761374, 0.495804539034,
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0.407050308965, 0.342353999733, 0.295530605237}};
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float csf_cr420[8][8] = {
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{2.03871978502, 2.62502345193, 1.26180942886, 1.11019789803, 1.01397751469,
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0.867069376285, 0.721500455585, 0.593906509971}, {2.62502345193,
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1.69112867013, 1.17180569821, 1.3342742857, 1.28513006198,
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1.13381474809, 0.962064122248, 0.802254508198}, {1.26180942886,
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1.17180569821, 0.944981930573, 0.990876405848, 0.995903384143,
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0.926972725286, 0.820534991409, 0.706020324706}, {1.11019789803,
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1.3342742857, 0.990876405848, 0.831632933426, 0.77418706195,
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0.725539939514, 0.661776842059, 0.587716619023}, {1.01397751469,
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1.28513006198, 0.995903384143, 0.77418706195, 0.653238524286,
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0.584635025748, 0.531064164893, 0.478717061273}, {0.867069376285,
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1.13381474809, 0.926972725286, 0.725539939514, 0.584635025748,
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0.496936637883, 0.438694579826, 0.393021669543}, {0.721500455585,
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0.962064122248, 0.820534991409, 0.661776842059, 0.531064164893,
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0.438694579826, 0.375820256136, 0.330555063063}, {0.593906509971,
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0.802254508198, 0.706020324706, 0.587716619023, 0.478717061273,
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0.393021669543, 0.330555063063, 0.285345396658}};
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static double convert_score_db(double _score, double _weight) {
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return 10 * (log10(255 * 255) - log10(_weight * _score));
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}
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static double calc_psnrhvs(const unsigned char *_src, int _systride,
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const unsigned char *_dst, int _dystride,
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double _par, int _w, int _h, int _step,
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float _csf[8][8]) {
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float ret;
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od_coeff dct_s[8 * 8];
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od_coeff dct_d[8 * 8];
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float mask[8][8];
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int pixels;
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int x;
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int y;
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(void) _par;
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ret = pixels = 0;
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/*In the PSNR-HVS-M paper[1] the authors describe the construction of
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their masking table as "we have used the quantization table for the
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color component Y of JPEG [6] that has been also obtained on the
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basis of CSF. Note that the values in quantization table JPEG have
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been normalized and then squared." Their CSF matrix (from PSNR-HVS)
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was also constructed from the JPEG matrices. I can not find any obvious
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scheme of normalizing to produce their table, but if I multiply their
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CSF by 0.38857 and square the result I get their masking table.
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I have no idea where this constant comes from, but deviating from it
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too greatly hurts MOS agreement.
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[1] Nikolay Ponomarenko, Flavia Silvestri, Karen Egiazarian, Marco Carli,
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Jaakko Astola, Vladimir Lukin, "On between-coefficient contrast masking
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of DCT basis functions", CD-ROM Proceedings of the Third
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International Workshop on Video Processing and Quality Metrics for Consumer
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Electronics VPQM-07, Scottsdale, Arizona, USA, 25-26 January, 2007, 4 p.*/
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for (x = 0; x < 8; x++)
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for (y = 0; y < 8; y++)
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mask[x][y] = (_csf[x][y] * 0.3885746225901003)
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* (_csf[x][y] * 0.3885746225901003);
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for (y = 0; y < _h - 7; y += _step) {
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for (x = 0; x < _w - 7; x += _step) {
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int i;
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int j;
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float s_means[4];
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float d_means[4];
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float s_vars[4];
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float d_vars[4];
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float s_gmean = 0;
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float d_gmean = 0;
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float s_gvar = 0;
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float d_gvar = 0;
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float s_mask = 0;
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float d_mask = 0;
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for (i = 0; i < 4; i++)
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s_means[i] = d_means[i] = s_vars[i] = d_vars[i] = 0;
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for (i = 0; i < 8; i++) {
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for (j = 0; j < 8; j++) {
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int sub = ((i & 12) >> 2) + ((j & 12) >> 1);
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dct_s[i * 8 + j] = _src[(y + i) * _systride + (j + x)];
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dct_d[i * 8 + j] = _dst[(y + i) * _dystride + (j + x)];
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s_gmean += dct_s[i * 8 + j];
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d_gmean += dct_d[i * 8 + j];
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s_means[sub] += dct_s[i * 8 + j];
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d_means[sub] += dct_d[i * 8 + j];
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}
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}
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s_gmean /= 64.f;
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d_gmean /= 64.f;
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for (i = 0; i < 4; i++)
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s_means[i] /= 16.f;
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for (i = 0; i < 4; i++)
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d_means[i] /= 16.f;
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for (i = 0; i < 8; i++) {
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for (j = 0; j < 8; j++) {
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int sub = ((i & 12) >> 2) + ((j & 12) >> 1);
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s_gvar += (dct_s[i * 8 + j] - s_gmean) * (dct_s[i * 8 + j] - s_gmean);
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d_gvar += (dct_d[i * 8 + j] - d_gmean) * (dct_d[i * 8 + j] - d_gmean);
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s_vars[sub] += (dct_s[i * 8 + j] - s_means[sub])
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* (dct_s[i * 8 + j] - s_means[sub]);
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d_vars[sub] += (dct_d[i * 8 + j] - d_means[sub])
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* (dct_d[i * 8 + j] - d_means[sub]);
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}
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}
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s_gvar *= 1 / 63.f * 64;
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d_gvar *= 1 / 63.f * 64;
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for (i = 0; i < 4; i++)
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s_vars[i] *= 1 / 15.f * 16;
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for (i = 0; i < 4; i++)
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d_vars[i] *= 1 / 15.f * 16;
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if (s_gvar > 0)
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s_gvar = (s_vars[0] + s_vars[1] + s_vars[2] + s_vars[3]) / s_gvar;
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if (d_gvar > 0)
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d_gvar = (d_vars[0] + d_vars[1] + d_vars[2] + d_vars[3]) / d_gvar;
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od_bin_fdct8x8(dct_s, 8, dct_s, 8);
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od_bin_fdct8x8(dct_d, 8, dct_d, 8);
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for (i = 0; i < 8; i++)
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for (j = (i == 0); j < 8; j++)
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s_mask += dct_s[i * 8 + j] * dct_s[i * 8 + j] * mask[i][j];
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for (i = 0; i < 8; i++)
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for (j = (i == 0); j < 8; j++)
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d_mask += dct_d[i * 8 + j] * dct_d[i * 8 + j] * mask[i][j];
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s_mask = sqrt(s_mask * s_gvar) / 32.f;
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d_mask = sqrt(d_mask * d_gvar) / 32.f;
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if (d_mask > s_mask)
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s_mask = d_mask;
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for (i = 0; i < 8; i++) {
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for (j = 0; j < 8; j++) {
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float err;
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err = fabs(dct_s[i * 8 + j] - dct_d[i * 8 + j]);
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if (i != 0 || j != 0)
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err = err < s_mask / mask[i][j] ? 0 : err - s_mask / mask[i][j];
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ret += (err * _csf[i][j]) * (err * _csf[i][j]);
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pixels++;
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}
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}
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}
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}
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ret /= pixels;
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return ret;
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}
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double vp9_psnrhvs(YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest,
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double *y_psnrhvs, double *u_psnrhvs, double *v_psnrhvs) {
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double psnrhvs;
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double par = 1.0;
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int step = 7;
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vp9_clear_system_state();
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*y_psnrhvs = calc_psnrhvs(source->y_buffer, source->y_stride, dest->y_buffer,
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dest->y_stride, par, source->y_crop_width,
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source->y_crop_height, step, csf_y);
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*u_psnrhvs = calc_psnrhvs(source->u_buffer, source->uv_stride, dest->u_buffer,
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dest->uv_stride, par, source->uv_crop_width,
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source->uv_crop_height, step, csf_cb420);
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*v_psnrhvs = calc_psnrhvs(source->v_buffer, source->uv_stride, dest->v_buffer,
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dest->uv_stride, par, source->uv_crop_width,
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source->uv_crop_height, step, csf_cr420);
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psnrhvs = (*y_psnrhvs) * .8 + .1 * ((*u_psnrhvs) + (*v_psnrhvs));
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return convert_score_db(psnrhvs, 1.0);
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}
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