15a50414796e9a458925c7a13a15055d02406bf43Vikas Arora// Copyright 2011 Google Inc. All Rights Reserved. 27c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 37c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// This code is licensed under the same terms as WebM: 47c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Software License Agreement: http://www.webmproject.org/license/software/ 57c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Additional IP Rights Grant: http://www.webmproject.org/license/additional/ 67c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// ----------------------------------------------------------------------------- 77c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 87c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Macroblock analysis 97c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Author: Skal (pascal.massimino@gmail.com) 117c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <stdlib.h> 137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <string.h> 147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <assert.h> 157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 165a50414796e9a458925c7a13a15055d02406bf43Vikas Arora#include "./vp8enci.h" 175a50414796e9a458925c7a13a15055d02406bf43Vikas Arora#include "./cost.h" 185a50414796e9a458925c7a13a15055d02406bf43Vikas Arora#include "../utils/utils.h" 197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#if defined(__cplusplus) || defined(c_plusplus) 217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Aroraextern "C" { 227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#endif 237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_ITERS_K_MEANS 6 257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int ClipAlpha(int alpha) { 277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return alpha < 0 ? 0 : alpha > 255 ? 255 : alpha; 287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 305a50414796e9a458925c7a13a15055d02406bf43Vikas Arora//------------------------------------------------------------------------------ 317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Smooth the segment map by replacing isolated block by the majority of its 327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// neighbours. 337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void SmoothSegmentMap(VP8Encoder* const enc) { 357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int n, x, y; 367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int w = enc->mb_w_; 377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int h = enc->mb_h_; 387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int majority_cnt_3_x_3_grid = 5; 395a50414796e9a458925c7a13a15055d02406bf43Vikas Arora uint8_t* const tmp = (uint8_t*)WebPSafeMalloc((uint64_t)w * h, sizeof(*tmp)); 405a50414796e9a458925c7a13a15055d02406bf43Vikas Arora assert((uint64_t)(w * h) == (uint64_t)w * h); // no overflow, as per spec 417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (tmp == NULL) return; 437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (y = 1; y < h - 1; ++y) { 447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (x = 1; x < w - 1; ++x) { 457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int cnt[NUM_MB_SEGMENTS] = { 0 }; 467c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8MBInfo* const mb = &enc->mb_info_[x + w * y]; 477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int majority_seg = mb->segment_; 487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Check the 8 neighbouring segment values. 497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w - 1].segment_]++; // top-left 507c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w + 0].segment_]++; // top 517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w + 1].segment_]++; // top-right 52466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ - 1].segment_]++; // left 53466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ + 1].segment_]++; // right 54466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w - 1].segment_]++; // bottom-left 55466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w + 0].segment_]++; // bottom 56466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w + 1].segment_]++; // bottom-right 577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < NUM_MB_SEGMENTS; ++n) { 587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (cnt[n] >= majority_cnt_3_x_3_grid) { 597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora majority_seg = n; 607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora tmp[x + y * w] = majority_seg; 637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (y = 1; y < h - 1; ++y) { 667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (x = 1; x < w - 1; ++x) { 677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MBInfo* const mb = &enc->mb_info_[x + w * y]; 687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora mb->segment_ = tmp[x + y * w]; 697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora free(tmp); 727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 745a50414796e9a458925c7a13a15055d02406bf43Vikas Arora//------------------------------------------------------------------------------ 757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Finalize Segment probability based on the coding tree 767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int GetProba(int a, int b) { 787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int proba; 797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int total = a + b; 807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (total == 0) return 255; // that's the default probability. 817c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora proba = (255 * a + total / 2) / total; 827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return proba; 837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void SetSegmentProbas(VP8Encoder* const enc) { 867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int p[NUM_MB_SEGMENTS] = { 0 }; 877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int n; 887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8MBInfo* const mb = &enc->mb_info_[n]; 917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora p[mb->segment_]++; 927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (enc->pic_->stats) { 947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < NUM_MB_SEGMENTS; ++n) { 957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->pic_->stats->segment_size[n] = p[n]; 967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (enc->segment_hdr_.num_segments_ > 1) { 997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora uint8_t* const probas = enc->proba_.segments_; 1007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora probas[0] = GetProba(p[0] + p[1], p[2] + p[3]); 1017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora probas[1] = GetProba(p[0], p[1]); 1027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora probas[2] = GetProba(p[2], p[3]); 1037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->segment_hdr_.update_map_ = 1057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora (probas[0] != 255) || (probas[1] != 255) || (probas[2] != 255); 1067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->segment_hdr_.size_ = 1077c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora p[0] * (VP8BitCost(0, probas[0]) + VP8BitCost(0, probas[1])) + 1087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora p[1] * (VP8BitCost(0, probas[0]) + VP8BitCost(1, probas[1])) + 1097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora p[2] * (VP8BitCost(1, probas[0]) + VP8BitCost(0, probas[2])) + 1107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora p[3] * (VP8BitCost(1, probas[0]) + VP8BitCost(1, probas[2])); 1117c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } else { 1127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->segment_hdr_.update_map_ = 0; 1137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->segment_hdr_.size_ = 0; 1147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 1167c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1175a50414796e9a458925c7a13a15055d02406bf43Vikas Arorastatic WEBP_INLINE int clip(int v, int m, int M) { 1187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return v < m ? m : v > M ? M : v; 1197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 1207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void SetSegmentAlphas(VP8Encoder* const enc, 1227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int centers[NUM_MB_SEGMENTS], 1237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mid) { 1247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int nb = enc->segment_hdr_.num_segments_; 1257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int min = centers[0], max = centers[0]; 1267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int n; 1277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (nb > 1) { 1297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (min > centers[n]) min = centers[n]; 1317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (max < centers[n]) max = centers[n]; 1327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (max == min) max = min + 1; 1357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora assert(mid <= max && mid >= min); 1367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int alpha = 255 * (centers[n] - mid) / (max - min); 1387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int beta = 255 * (centers[n] - min) / (max - min); 1397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->dqm_[n].alpha_ = clip(alpha, -127, 127); 1407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->dqm_[n].beta_ = clip(beta, 0, 255); 1417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 1437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1445a50414796e9a458925c7a13a15055d02406bf43Vikas Arora//------------------------------------------------------------------------------ 1457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Simplified k-Means, to assign Nb segments based on alpha-histogram 1467c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void AssignSegments(VP8Encoder* const enc, const int alphas[256]) { 1487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int nb = enc->segment_hdr_.num_segments_; 1497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int centers[NUM_MB_SEGMENTS]; 1505a50414796e9a458925c7a13a15055d02406bf43Vikas Arora int weighted_average = 0; 1517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int map[256]; 1527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int a, n, k; 1537c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int min_a = 0, max_a = 255, range_a; 1547c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // 'int' type is ok for histo, and won't overflow 1557c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS]; 1567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // bracket the input 1587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < 256 && alphas[n] == 0; ++n) {} 1597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora min_a = n; 1607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 255; n > min_a && alphas[n] == 0; --n) {} 1617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora max_a = n; 1627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora range_a = max_a - min_a; 1637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Spread initial centers evenly 1657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 1, k = 0; n < 2 * nb; n += 2) { 1667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora centers[k++] = min_a + (n * range_a) / (2 * nb); 1677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (k = 0; k < MAX_ITERS_K_MEANS; ++k) { // few iters are enough 1707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int total_weight; 1717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int displaced; 1727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Reset stats 1737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] = 0; 1757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] = 0; 1767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Assign nearest center for each 'a' 1787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n = 0; // track the nearest center for current 'a' 1797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (a = min_a; a <= max_a; ++a) { 1807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alphas[a]) { 1817c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora while (n < nb - 1 && abs(a - centers[n + 1]) < abs(a - centers[n])) { 1827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n++; 1837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora map[a] = n; 1857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // accumulate contribution into best centroid 1867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] += a * alphas[a]; 1877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] += alphas[a]; 1887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // All point are classified. Move the centroids to the 1917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // center of their respective cloud. 1927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced = 0; 1937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = 0; 1947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight = 0; 1957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (accum[n]) { 1977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int new_center = (dist_accum[n] + accum[n] / 2) / accum[n]; 1987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced += abs(centers[n] - new_center); 1997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora centers[n] = new_center; 2007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average += new_center * accum[n]; 2017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight += accum[n]; 2027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = (weighted_average + total_weight / 2) / total_weight; 2057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (displaced < 5) break; // no need to keep on looping... 2067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2077c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Map each original value to the closest centroid 2097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 2107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MBInfo* const mb = &enc->mb_info_[n]; 2115a50414796e9a458925c7a13a15055d02406bf43Vikas Arora const int alpha = mb->alpha_; 2125a50414796e9a458925c7a13a15055d02406bf43Vikas Arora mb->segment_ = map[alpha]; 2135a50414796e9a458925c7a13a15055d02406bf43Vikas Arora mb->alpha_ = centers[map[alpha]]; // just for the record. 2147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2167c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (nb > 1) { 2177c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int smooth = (enc->config_->preprocessing & 1); 2187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (smooth) SmoothSegmentMap(enc); 2197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora SetSegmentProbas(enc); // Assign final proba 2227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora SetSegmentAlphas(enc, centers, weighted_average); // pick some alphas. 2237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2255a50414796e9a458925c7a13a15055d02406bf43Vikas Arora//------------------------------------------------------------------------------ 2267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Macroblock analysis: collect histogram for each mode, deduce the maximal 2277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// susceptibility and set best modes for this macroblock. 2287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Segment assignment is done later. 2297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Number of modes to inspect for alpha_ evaluation. For high-quality settings, 2317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// we don't need to test all the possible modes during the analysis phase. 2327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA16_MODE 2 2337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA4_MODE 2 2347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_UV_MODE 2 2357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) { 2377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA16_MODE : 4; 2387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha = -1; 2407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 2417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeLuma16Preds(it); 2437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 244466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora const int alpha = VP8CollectHistogram(it->yuv_in_ + Y_OFF, 245466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora it->yuv_p_ + VP8I16ModeOffsets[mode], 246466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora 0, 16); 2477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alpha > best_alpha) { 2487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 2497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 2507c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, best_mode); 2537c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 2547c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2557c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it, 2577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha) { 2585a50414796e9a458925c7a13a15055d02406bf43Vikas Arora uint8_t modes[16]; 2597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA4_MODE : NUM_BMODES; 2607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int i4_alpha = 0; 2617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8IteratorStartI4(it); 2627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora do { 2637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode_alpha = -1; 2657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_]; 2667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeIntra4Preds(it); 2687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 269466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora const int alpha = VP8CollectHistogram(src, 270466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora it->yuv_p_ + VP8I4ModeOffsets[mode], 271466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora 0, 1); 2727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alpha > best_mode_alpha) { 2737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode_alpha = alpha; 2747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora modes[it->i4_] = mode; 2757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora i4_alpha += best_mode_alpha; 2787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Note: we reuse the original samples for predictors 2797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF)); 2807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2817c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (i4_alpha > best_alpha) { 2827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra4Mode(it, modes); 2837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = ClipAlpha(i4_alpha); 2847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 2867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestUVMode(VP8EncIterator* const it) { 2897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha = -1; 2907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 2917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int max_mode = (it->enc_->method_ >= 3) ? MAX_UV_MODE : 4; 2927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeChroma8Preds(it); 2947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 295466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora const int alpha = VP8CollectHistogram(it->yuv_in_ + U_OFF, 296466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora it->yuv_p_ + VP8UVModeOffsets[mode], 297466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora 16, 16 + 4 + 4); 2987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alpha > best_alpha) { 2997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 3007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 3017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntraUVMode(it, best_mode); 3047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 3057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3077c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void MBAnalyze(VP8EncIterator* const it, 3087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int alphas[256], int* const uv_alpha) { 3097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8Encoder* const enc = it->enc_; 3107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha, best_uv_alpha; 3117c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, 0); // default: Intra16, DC_PRED 3137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSkip(it, 0); // not skipped 3147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSegment(it, 0); // default segment, spec-wise. 3157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3167c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra16Mode(it); 3177c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (enc->method_ != 3) { 3187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // We go and make a fast decision for intra4/intra16. 3197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // It's usually not a good and definitive pick, but helps seeding the stats 3207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // about level bit-cost. 3217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // TODO(skal): improve criterion. 3227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra4Mode(it, best_alpha); 3237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_uv_alpha = MBAnalyzeBestUVMode(it); 3257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Final susceptibility mix 3277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = (best_alpha + best_uv_alpha + 1) / 2; 3287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora alphas[best_alpha]++; 3297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora *uv_alpha += best_uv_alpha; 3307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora it->mb_->alpha_ = best_alpha; // Informative only. 3317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3335a50414796e9a458925c7a13a15055d02406bf43Vikas Arora//------------------------------------------------------------------------------ 3347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Main analysis loop: 3357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Collect all susceptibilities for each macroblock and record their 3367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// distribution in alphas[]. Segments is assigned a-posteriori, based on 3377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this histogram. 3387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// We also pick an intra16 prediction mode, which shouldn't be considered 3397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// final except for fast-encode settings. We can also pick some intra4 modes 3407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// and decide intra4/intra16, but that's usually almost always a bad choice at 3417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this stage. 3427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Aroraint VP8EncAnalyze(VP8Encoder* const enc) { 3445a50414796e9a458925c7a13a15055d02406bf43Vikas Arora int ok = 1; 3457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int alphas[256] = { 0 }; 3467c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8EncIterator it; 3477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8IteratorInit(enc, &it); 3497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->uv_alpha_ = 0; 3507c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora do { 3517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8IteratorImport(&it); 3527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora MBAnalyze(&it, alphas, &enc->uv_alpha_); 3535a50414796e9a458925c7a13a15055d02406bf43Vikas Arora ok = VP8IteratorProgress(&it, 20); 3547c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Let's pretend we have perfect lossless reconstruction. 3555a50414796e9a458925c7a13a15055d02406bf43Vikas Arora } while (ok && VP8IteratorNext(&it, it.yuv_in_)); 3567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->uv_alpha_ /= enc->mb_w_ * enc->mb_h_; 3575a50414796e9a458925c7a13a15055d02406bf43Vikas Arora if (ok) AssignSegments(enc, alphas); 3587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3595a50414796e9a458925c7a13a15055d02406bf43Vikas Arora return ok; 3607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#if defined(__cplusplus) || defined(c_plusplus) 3637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} // extern "C" 3647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#endif 365