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Nagram/TMessagesProj/jni/libwebp/dsp/lossless.c

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Update to 2.3.0
2015-01-02 22:15:07 +00:00
// Copyright 2012 Google Inc. All Rights Reserved.
//
// Use of this source code is governed by a BSD-style license
// that can be found in the COPYING 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.
// -----------------------------------------------------------------------------
//
// Image transforms and color space conversion methods for lossless decoder.
//
// Authors: Vikas Arora (vikaas.arora@gmail.com)
// Jyrki Alakuijala (jyrki@google.com)
// Urvang Joshi (urvang@google.com)
#include "./dsp.h"
#include <math.h>
#include <stdlib.h>
#include "../dec/vp8li.h"
#include "../utils/endian_inl.h"
#include "./lossless.h"
#include "./yuv.h"
#define MAX_DIFF_COST (1e30f)
// lookup table for small values of log2(int)
const float kLog2Table[LOG_LOOKUP_IDX_MAX] = {
0.0000000000000000f, 0.0000000000000000f,
1.0000000000000000f, 1.5849625007211560f,
2.0000000000000000f, 2.3219280948873621f,
2.5849625007211560f, 2.8073549220576041f,
3.0000000000000000f, 3.1699250014423121f,
3.3219280948873621f, 3.4594316186372973f,
3.5849625007211560f, 3.7004397181410921f,
3.8073549220576041f, 3.9068905956085187f,
4.0000000000000000f, 4.0874628412503390f,
4.1699250014423121f, 4.2479275134435852f,
4.3219280948873626f, 4.3923174227787606f,
4.4594316186372973f, 4.5235619560570130f,
4.5849625007211560f, 4.6438561897747243f,
4.7004397181410917f, 4.7548875021634682f,
4.8073549220576037f, 4.8579809951275718f,
4.9068905956085187f, 4.9541963103868749f,
5.0000000000000000f, 5.0443941193584533f,
5.0874628412503390f, 5.1292830169449663f,
5.1699250014423121f, 5.2094533656289501f,
5.2479275134435852f, 5.2854022188622487f,
5.3219280948873626f, 5.3575520046180837f,
5.3923174227787606f, 5.4262647547020979f,
5.4594316186372973f, 5.4918530963296747f,
5.5235619560570130f, 5.5545888516776376f,
5.5849625007211560f, 5.6147098441152083f,
5.6438561897747243f, 5.6724253419714951f,
5.7004397181410917f, 5.7279204545631987f,
5.7548875021634682f, 5.7813597135246599f,
5.8073549220576037f, 5.8328900141647412f,
5.8579809951275718f, 5.8826430493618415f,
5.9068905956085187f, 5.9307373375628866f,
5.9541963103868749f, 5.9772799234999167f,
6.0000000000000000f, 6.0223678130284543f,
6.0443941193584533f, 6.0660891904577720f,
6.0874628412503390f, 6.1085244567781691f,
6.1292830169449663f, 6.1497471195046822f,
6.1699250014423121f, 6.1898245588800175f,
6.2094533656289501f, 6.2288186904958804f,
6.2479275134435852f, 6.2667865406949010f,
6.2854022188622487f, 6.3037807481771030f,
6.3219280948873626f, 6.3398500028846243f,
6.3575520046180837f, 6.3750394313469245f,
6.3923174227787606f, 6.4093909361377017f,
6.4262647547020979f, 6.4429434958487279f,
6.4594316186372973f, 6.4757334309663976f,
6.4918530963296747f, 6.5077946401986963f,
6.5235619560570130f, 6.5391588111080309f,
6.5545888516776376f, 6.5698556083309478f,
6.5849625007211560f, 6.5999128421871278f,
6.6147098441152083f, 6.6293566200796094f,
6.6438561897747243f, 6.6582114827517946f,
6.6724253419714951f, 6.6865005271832185f,
6.7004397181410917f, 6.7142455176661224f,
6.7279204545631987f, 6.7414669864011464f,
6.7548875021634682f, 6.7681843247769259f,
6.7813597135246599f, 6.7944158663501061f,
6.8073549220576037f, 6.8201789624151878f,
6.8328900141647412f, 6.8454900509443747f,
6.8579809951275718f, 6.8703647195834047f,
6.8826430493618415f, 6.8948177633079437f,
6.9068905956085187f, 6.9188632372745946f,
6.9307373375628866f, 6.9425145053392398f,
6.9541963103868749f, 6.9657842846620869f,
6.9772799234999167f, 6.9886846867721654f,
7.0000000000000000f, 7.0112272554232539f,
7.0223678130284543f, 7.0334230015374501f,
7.0443941193584533f, 7.0552824355011898f,
7.0660891904577720f, 7.0768155970508308f,
7.0874628412503390f, 7.0980320829605263f,
7.1085244567781691f, 7.1189410727235076f,
7.1292830169449663f, 7.1395513523987936f,
7.1497471195046822f, 7.1598713367783890f,
7.1699250014423121f, 7.1799090900149344f,
7.1898245588800175f, 7.1996723448363644f,
7.2094533656289501f, 7.2191685204621611f,
7.2288186904958804f, 7.2384047393250785f,
7.2479275134435852f, 7.2573878426926521f,
7.2667865406949010f, 7.2761244052742375f,
7.2854022188622487f, 7.2946207488916270f,
7.3037807481771030f, 7.3128829552843557f,
7.3219280948873626f, 7.3309168781146167f,
7.3398500028846243f, 7.3487281542310771f,
7.3575520046180837f, 7.3663222142458160f,
7.3750394313469245f, 7.3837042924740519f,
7.3923174227787606f, 7.4008794362821843f,
7.4093909361377017f, 7.4178525148858982f,
7.4262647547020979f, 7.4346282276367245f,
7.4429434958487279f, 7.4512111118323289f,
7.4594316186372973f, 7.4676055500829976f,
7.4757334309663976f, 7.4838157772642563f,
7.4918530963296747f, 7.4998458870832056f,
7.5077946401986963f, 7.5156998382840427f,
7.5235619560570130f, 7.5313814605163118f,
7.5391588111080309f, 7.5468944598876364f,
7.5545888516776376f, 7.5622424242210728f,
7.5698556083309478f, 7.5774288280357486f,
7.5849625007211560f, 7.5924570372680806f,
7.5999128421871278f, 7.6073303137496104f,
7.6147098441152083f, 7.6220518194563764f,
7.6293566200796094f, 7.6366246205436487f,
7.6438561897747243f, 7.6510516911789281f,
7.6582114827517946f, 7.6653359171851764f,
7.6724253419714951f, 7.6794800995054464f,
7.6865005271832185f, 7.6934869574993252f,
7.7004397181410917f, 7.7073591320808825f,
7.7142455176661224f, 7.7210991887071855f,
7.7279204545631987f, 7.7347096202258383f,
7.7414669864011464f, 7.7481928495894605f,
7.7548875021634682f, 7.7615512324444795f,
7.7681843247769259f, 7.7747870596011736f,
7.7813597135246599f, 7.7879025593914317f,
7.7944158663501061f, 7.8008998999203047f,
7.8073549220576037f, 7.8137811912170374f,
7.8201789624151878f, 7.8265484872909150f,
7.8328900141647412f, 7.8392037880969436f,
7.8454900509443747f, 7.8517490414160571f,
7.8579809951275718f, 7.8641861446542797f,
7.8703647195834047f, 7.8765169465649993f,
7.8826430493618415f, 7.8887432488982591f,
7.8948177633079437f, 7.9008668079807486f,
7.9068905956085187f, 7.9128893362299619f,
7.9188632372745946f, 7.9248125036057812f,
7.9307373375628866f, 7.9366379390025709f,
7.9425145053392398f, 7.9483672315846778f,
7.9541963103868749f, 7.9600019320680805f,
7.9657842846620869f, 7.9715435539507719f,
7.9772799234999167f, 7.9829935746943103f,
7.9886846867721654f, 7.9943534368588577f
};
const float kSLog2Table[LOG_LOOKUP_IDX_MAX] = {
0.00000000f, 0.00000000f, 2.00000000f, 4.75488750f,
8.00000000f, 11.60964047f, 15.50977500f, 19.65148445f,
24.00000000f, 28.52932501f, 33.21928095f, 38.05374781f,
43.01955001f, 48.10571634f, 53.30296891f, 58.60335893f,
64.00000000f, 69.48686830f, 75.05865003f, 80.71062276f,
86.43856190f, 92.23866588f, 98.10749561f, 104.04192499f,
110.03910002f, 116.09640474f, 122.21143267f, 128.38196256f,
134.60593782f, 140.88144886f, 147.20671787f, 153.58008562f,
160.00000000f, 166.46500594f, 172.97373660f, 179.52490559f,
186.11730005f, 192.74977453f, 199.42124551f, 206.13068654f,
212.87712380f, 219.65963219f, 226.47733176f, 233.32938445f,
240.21499122f, 247.13338933f, 254.08384998f, 261.06567603f,
268.07820003f, 275.12078236f, 282.19280949f, 289.29369244f,
296.42286534f, 303.57978409f, 310.76392512f, 317.97478424f,
325.21187564f, 332.47473081f, 339.76289772f, 347.07593991f,
354.41343574f, 361.77497759f, 369.16017124f, 376.56863518f,
384.00000000f, 391.45390785f, 398.93001188f, 406.42797576f,
413.94747321f, 421.48818752f, 429.04981119f, 436.63204548f,
444.23460010f, 451.85719280f, 459.49954906f, 467.16140179f,
474.84249102f, 482.54256363f, 490.26137307f, 497.99867911f,
505.75424759f, 513.52785023f, 521.31926438f, 529.12827280f,
536.95466351f, 544.79822957f, 552.65876890f, 560.53608414f,
568.42998244f, 576.34027536f, 584.26677867f, 592.20931226f,
600.16769996f, 608.14176943f, 616.13135206f, 624.13628279f,
632.15640007f, 640.19154569f, 648.24156472f, 656.30630539f,
664.38561898f, 672.47935976f, 680.58738488f, 688.70955430f,
696.84573069f, 704.99577935f, 713.15956818f, 721.33696754f,
729.52785023f, 737.73209140f, 745.94956849f, 754.18016116f,
762.42375127f, 770.68022275f, 778.94946161f, 787.23135586f,
795.52579543f, 803.83267219f, 812.15187982f, 820.48331383f,
828.82687147f, 837.18245171f, 845.54995518f, 853.92928416f,
862.32034249f, 870.72303558f, 879.13727036f, 887.56295522f,
896.00000000f, 904.44831595f, 912.90781569f, 921.37841320f,
929.86002376f, 938.35256392f, 946.85595152f, 955.37010560f,
963.89494641f, 972.43039537f, 980.97637504f, 989.53280911f,
998.09962237f, 1006.67674069f, 1015.26409097f, 1023.86160116f,
1032.46920021f, 1041.08681805f, 1049.71438560f, 1058.35183469f,
1066.99909811f, 1075.65610955f, 1084.32280357f, 1092.99911564f,
1101.68498204f, 1110.38033993f, 1119.08512727f, 1127.79928282f,
1136.52274614f, 1145.25545758f, 1153.99735821f, 1162.74838989f,
1171.50849518f, 1180.27761738f, 1189.05570047f, 1197.84268914f,
1206.63852876f, 1215.44316535f, 1224.25654560f, 1233.07861684f,
1241.90932703f, 1250.74862473f, 1259.59645914f, 1268.45278005f,
1277.31753781f, 1286.19068338f, 1295.07216828f, 1303.96194457f,
1312.85996488f, 1321.76618236f, 1330.68055071f, 1339.60302413f,
1348.53355734f, 1357.47210556f, 1366.41862452f, 1375.37307041f,
1384.33539991f, 1393.30557020f, 1402.28353887f, 1411.26926400f,
1420.26270412f, 1429.26381818f, 1438.27256558f, 1447.28890615f,
1456.31280014f, 1465.34420819f, 1474.38309138f, 1483.42941118f,
1492.48312945f, 1501.54420843f, 1510.61261078f, 1519.68829949f,
1528.77123795f, 1537.86138993f, 1546.95871952f, 1556.06319119f,
1565.17476976f, 1574.29342040f, 1583.41910860f, 1592.55180020f,
1601.69146137f, 1610.83805860f, 1619.99155871f, 1629.15192882f,
1638.31913637f, 1647.49314911f, 1656.67393509f, 1665.86146266f,
1675.05570047f, 1684.25661744f, 1693.46418280f, 1702.67836605f,
1711.89913698f, 1721.12646563f, 1730.36032233f, 1739.60067768f,
1748.84750254f, 1758.10076802f, 1767.36044551f, 1776.62650662f,
1785.89892323f, 1795.17766747f, 1804.46271172f, 1813.75402857f,
1823.05159087f, 1832.35537170f, 1841.66534438f, 1850.98148244f,
1860.30375965f, 1869.63214999f, 1878.96662767f, 1888.30716711f,
1897.65374295f, 1907.00633003f, 1916.36490342f, 1925.72943838f,
1935.09991037f, 1944.47629506f, 1953.85856831f, 1963.24670620f,
1972.64068498f, 1982.04048108f, 1991.44607117f, 2000.85743204f,
2010.27454072f, 2019.69737440f, 2029.12591044f, 2038.56012640f
};
const VP8LPrefixCode kPrefixEncodeCode[PREFIX_LOOKUP_IDX_MAX] = {
{ 0, 0}, { 0, 0}, { 1, 0}, { 2, 0}, { 3, 0}, { 4, 1}, { 4, 1}, { 5, 1},
{ 5, 1}, { 6, 2}, { 6, 2}, { 6, 2}, { 6, 2}, { 7, 2}, { 7, 2}, { 7, 2},
{ 7, 2}, { 8, 3}, { 8, 3}, { 8, 3}, { 8, 3}, { 8, 3}, { 8, 3}, { 8, 3},
{ 8, 3}, { 9, 3}, { 9, 3}, { 9, 3}, { 9, 3}, { 9, 3}, { 9, 3}, { 9, 3},
{ 9, 3}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4},
{10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4}, {10, 4},
{10, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4},
{11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4}, {11, 4},
{11, 4}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5},
{12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5},
{12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5},
{12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5}, {12, 5},
{12, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5},
{13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5},
{13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5},
{13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5}, {13, 5},
{13, 5}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6}, {14, 6},
{14, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6}, {15, 6},
{15, 6}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7}, {16, 7},
{16, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
{17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7}, {17, 7},
};
const uint8_t kPrefixEncodeExtraBitsValue[PREFIX_LOOKUP_IDX_MAX] = {
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 2, 3, 0, 1, 2, 3,
0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95,
96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,
112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126,
127,
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95,
96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,
112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126
};
// The threshold till approximate version of log_2 can be used.
// Practically, we can get rid of the call to log() as the two values match to
// very high degree (the ratio of these two is 0.99999x).
// Keeping a high threshold for now.
#define APPROX_LOG_WITH_CORRECTION_MAX 65536
#define APPROX_LOG_MAX 4096
#define LOG_2_RECIPROCAL 1.44269504088896338700465094007086
static float FastSLog2Slow(uint32_t v) {
assert(v >= LOG_LOOKUP_IDX_MAX);
if (v < APPROX_LOG_WITH_CORRECTION_MAX) {
int log_cnt = 0;
uint32_t y = 1;
int correction = 0;
const float v_f = (float)v;
const uint32_t orig_v = v;
do {
++log_cnt;
v = v >> 1;
y = y << 1;
} while (v >= LOG_LOOKUP_IDX_MAX);
// vf = (2^log_cnt) * Xf; where y = 2^log_cnt and Xf < 256
// Xf = floor(Xf) * (1 + (v % y) / v)
// log2(Xf) = log2(floor(Xf)) + log2(1 + (v % y) / v)
// The correction factor: log(1 + d) ~ d; for very small d values, so
// log2(1 + (v % y) / v) ~ LOG_2_RECIPROCAL * (v % y)/v
// LOG_2_RECIPROCAL ~ 23/16
correction = (23 * (orig_v & (y - 1))) >> 4;
return v_f * (kLog2Table[v] + log_cnt) + correction;
} else {
return (float)(LOG_2_RECIPROCAL * v * log((double)v));
}
}
static float FastLog2Slow(uint32_t v) {
assert(v >= LOG_LOOKUP_IDX_MAX);
if (v < APPROX_LOG_WITH_CORRECTION_MAX) {
int log_cnt = 0;
uint32_t y = 1;
const uint32_t orig_v = v;
double log_2;
do {
++log_cnt;
v = v >> 1;
y = y << 1;
} while (v >= LOG_LOOKUP_IDX_MAX);
log_2 = kLog2Table[v] + log_cnt;
if (orig_v >= APPROX_LOG_MAX) {
// Since the division is still expensive, add this correction factor only
// for large values of 'v'.
const int correction = (23 * (orig_v & (y - 1))) >> 4;
log_2 += (double)correction / orig_v;
}
return (float)log_2;
} else {
return (float)(LOG_2_RECIPROCAL * log((double)v));
}
}
//------------------------------------------------------------------------------
// Image transforms.
// Mostly used to reduce code size + readability
static WEBP_INLINE int GetMin(int a, int b) { return (a > b) ? b : a; }
// In-place sum of each component with mod 256.
static WEBP_INLINE void AddPixelsEq(uint32_t* a, uint32_t b) {
const uint32_t alpha_and_green = (*a & 0xff00ff00u) + (b & 0xff00ff00u);
const uint32_t red_and_blue = (*a & 0x00ff00ffu) + (b & 0x00ff00ffu);
*a = (alpha_and_green & 0xff00ff00u) | (red_and_blue & 0x00ff00ffu);
}
static WEBP_INLINE uint32_t Average2(uint32_t a0, uint32_t a1) {
return (((a0 ^ a1) & 0xfefefefeL) >> 1) + (a0 & a1);
}
static WEBP_INLINE uint32_t Average3(uint32_t a0, uint32_t a1, uint32_t a2) {
return Average2(Average2(a0, a2), a1);
}
static WEBP_INLINE uint32_t Average4(uint32_t a0, uint32_t a1,
uint32_t a2, uint32_t a3) {
return Average2(Average2(a0, a1), Average2(a2, a3));
}
static WEBP_INLINE uint32_t Clip255(uint32_t a) {
if (a < 256) {
return a;
}
// return 0, when a is a negative integer.
// return 255, when a is positive.
return ~a >> 24;
}
static WEBP_INLINE int AddSubtractComponentFull(int a, int b, int c) {
return Clip255(a + b - c);
}
static WEBP_INLINE uint32_t ClampedAddSubtractFull(uint32_t c0, uint32_t c1,
uint32_t c2) {
const int a = AddSubtractComponentFull(c0 >> 24, c1 >> 24, c2 >> 24);
const int r = AddSubtractComponentFull((c0 >> 16) & 0xff,
(c1 >> 16) & 0xff,
(c2 >> 16) & 0xff);
const int g = AddSubtractComponentFull((c0 >> 8) & 0xff,
(c1 >> 8) & 0xff,
(c2 >> 8) & 0xff);
const int b = AddSubtractComponentFull(c0 & 0xff, c1 & 0xff, c2 & 0xff);
return ((uint32_t)a << 24) | (r << 16) | (g << 8) | b;
}
static WEBP_INLINE int AddSubtractComponentHalf(int a, int b) {
return Clip255(a + (a - b) / 2);
}
static WEBP_INLINE uint32_t ClampedAddSubtractHalf(uint32_t c0, uint32_t c1,
uint32_t c2) {
const uint32_t ave = Average2(c0, c1);
const int a = AddSubtractComponentHalf(ave >> 24, c2 >> 24);
const int r = AddSubtractComponentHalf((ave >> 16) & 0xff, (c2 >> 16) & 0xff);
const int g = AddSubtractComponentHalf((ave >> 8) & 0xff, (c2 >> 8) & 0xff);
const int b = AddSubtractComponentHalf((ave >> 0) & 0xff, (c2 >> 0) & 0xff);
return ((uint32_t)a << 24) | (r << 16) | (g << 8) | b;
}
// gcc-4.9 on ARM generates incorrect code in Select() when Sub3() is inlined.
#if defined(__arm__) && LOCAL_GCC_VERSION == 0x409
# define LOCAL_INLINE __attribute__ ((noinline))
#else
# define LOCAL_INLINE WEBP_INLINE
#endif
static LOCAL_INLINE int Sub3(int a, int b, int c) {
const int pb = b - c;
const int pa = a - c;
return abs(pb) - abs(pa);
}
#undef LOCAL_INLINE
static WEBP_INLINE uint32_t Select(uint32_t a, uint32_t b, uint32_t c) {
const int pa_minus_pb =
Sub3((a >> 24) , (b >> 24) , (c >> 24) ) +
Sub3((a >> 16) & 0xff, (b >> 16) & 0xff, (c >> 16) & 0xff) +
Sub3((a >> 8) & 0xff, (b >> 8) & 0xff, (c >> 8) & 0xff) +
Sub3((a ) & 0xff, (b ) & 0xff, (c ) & 0xff);
return (pa_minus_pb <= 0) ? a : b;
}
//------------------------------------------------------------------------------
// Predictors
static uint32_t Predictor0(uint32_t left, const uint32_t* const top) {
(void)top;
(void)left;
return ARGB_BLACK;
}
static uint32_t Predictor1(uint32_t left, const uint32_t* const top) {
(void)top;
return left;
}
static uint32_t Predictor2(uint32_t left, const uint32_t* const top) {
(void)left;
return top[0];
}
static uint32_t Predictor3(uint32_t left, const uint32_t* const top) {
(void)left;
return top[1];
}
static uint32_t Predictor4(uint32_t left, const uint32_t* const top) {
(void)left;
return top[-1];
}
static uint32_t Predictor5(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average3(left, top[0], top[1]);
return pred;
}
static uint32_t Predictor6(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(left, top[-1]);
return pred;
}
static uint32_t Predictor7(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(left, top[0]);
return pred;
}
static uint32_t Predictor8(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(top[-1], top[0]);
(void)left;
return pred;
}
static uint32_t Predictor9(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(top[0], top[1]);
(void)left;
return pred;
}
static uint32_t Predictor10(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average4(left, top[-1], top[0], top[1]);
return pred;
}
static uint32_t Predictor11(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Select(top[0], left, top[-1]);
return pred;
}
static uint32_t Predictor12(uint32_t left, const uint32_t* const top) {
const uint32_t pred = ClampedAddSubtractFull(left, top[0], top[-1]);
return pred;
}
static uint32_t Predictor13(uint32_t left, const uint32_t* const top) {
const uint32_t pred = ClampedAddSubtractHalf(left, top[0], top[-1]);
return pred;
}
static const VP8LPredictorFunc kPredictorsC[16] = {
Predictor0, Predictor1, Predictor2, Predictor3,
Predictor4, Predictor5, Predictor6, Predictor7,
Predictor8, Predictor9, Predictor10, Predictor11,
Predictor12, Predictor13,
Predictor0, Predictor0 // <- padding security sentinels
};
static float PredictionCostSpatial(const int counts[256], int weight_0,
double exp_val) {
const int significant_symbols = 256 >> 4;
const double exp_decay_factor = 0.6;
double bits = weight_0 * counts[0];
int i;
for (i = 1; i < significant_symbols; ++i) {
bits += exp_val * (counts[i] + counts[256 - i]);
exp_val *= exp_decay_factor;
}
return (float)(-0.1 * bits);
}
// Compute the combined Shanon's entropy for distribution {X} and {X+Y}
static float CombinedShannonEntropy(const int X[256], const int Y[256]) {
int i;
double retval = 0.;
int sumX = 0, sumXY = 0;
for (i = 0; i < 256; ++i) {
const int x = X[i];
const int xy = x + Y[i];
if (x != 0) {
sumX += x;
retval -= VP8LFastSLog2(x);
sumXY += xy;
retval -= VP8LFastSLog2(xy);
} else if (xy != 0) {
sumXY += xy;
retval -= VP8LFastSLog2(xy);
}
}
retval += VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY);
return (float)retval;
}
static float PredictionCostSpatialHistogram(const int accumulated[4][256],
const int tile[4][256]) {
int i;
double retval = 0;
for (i = 0; i < 4; ++i) {
const double kExpValue = 0.94;
retval += PredictionCostSpatial(tile[i], 1, kExpValue);
retval += CombinedShannonEntropy(tile[i], accumulated[i]);
}
return (float)retval;
}
static WEBP_INLINE void UpdateHisto(int histo_argb[4][256], uint32_t argb) {
++histo_argb[0][argb >> 24];
++histo_argb[1][(argb >> 16) & 0xff];
++histo_argb[2][(argb >> 8) & 0xff];
++histo_argb[3][argb & 0xff];
}
static int GetBestPredictorForTile(int width, int height,
int tile_x, int tile_y, int bits,
const int accumulated[4][256],
const uint32_t* const argb_scratch) {
const int kNumPredModes = 14;
const int col_start = tile_x << bits;
const int row_start = tile_y << bits;
const int tile_size = 1 << bits;
const int max_y = GetMin(tile_size, height - row_start);
const int max_x = GetMin(tile_size, width - col_start);
float best_diff = MAX_DIFF_COST;
int best_mode = 0;
int mode;
for (mode = 0; mode < kNumPredModes; ++mode) {
const uint32_t* current_row = argb_scratch;
const VP8LPredictorFunc pred_func = VP8LPredictors[mode];
float cur_diff;
int y;
int histo_argb[4][256];
memset(histo_argb, 0, sizeof(histo_argb));
for (y = 0; y < max_y; ++y) {
int x;
const int row = row_start + y;
const uint32_t* const upper_row = current_row;
current_row = upper_row + width;
for (x = 0; x < max_x; ++x) {
const int col = col_start + x;
uint32_t predict;
if (row == 0) {
predict = (col == 0) ? ARGB_BLACK : current_row[col - 1]; // Left.
} else if (col == 0) {
predict = upper_row[col]; // Top.
} else {
predict = pred_func(current_row[col - 1], upper_row + col);
}
UpdateHisto(histo_argb, VP8LSubPixels(current_row[col], predict));
}
}
cur_diff = PredictionCostSpatialHistogram(
accumulated, (const int (*)[256])histo_argb);
if (cur_diff < best_diff) {
best_diff = cur_diff;
best_mode = mode;
}
}
return best_mode;
}
static void CopyTileWithPrediction(int width, int height,
int tile_x, int tile_y, int bits, int mode,
const uint32_t* const argb_scratch,
uint32_t* const argb) {
const int col_start = tile_x << bits;
const int row_start = tile_y << bits;
const int tile_size = 1 << bits;
const int max_y = GetMin(tile_size, height - row_start);
const int max_x = GetMin(tile_size, width - col_start);
const VP8LPredictorFunc pred_func = VP8LPredictors[mode];
const uint32_t* current_row = argb_scratch;
int y;
for (y = 0; y < max_y; ++y) {
int x;
const int row = row_start + y;
const uint32_t* const upper_row = current_row;
current_row = upper_row + width;
for (x = 0; x < max_x; ++x) {
const int col = col_start + x;
const int pix = row * width + col;
uint32_t predict;
if (row == 0) {
predict = (col == 0) ? ARGB_BLACK : current_row[col - 1]; // Left.
} else if (col == 0) {
predict = upper_row[col]; // Top.
} else {
predict = pred_func(current_row[col - 1], upper_row + col);
}
argb[pix] = VP8LSubPixels(current_row[col], predict);
}
}
}
void VP8LResidualImage(int width, int height, int bits,
uint32_t* const argb, uint32_t* const argb_scratch,
uint32_t* const image) {
const int max_tile_size = 1 << bits;
const int tiles_per_row = VP8LSubSampleSize(width, bits);
const int tiles_per_col = VP8LSubSampleSize(height, bits);
uint32_t* const upper_row = argb_scratch;
uint32_t* const current_tile_rows = argb_scratch + width;
int tile_y;
int histo[4][256];
memset(histo, 0, sizeof(histo));
for (tile_y = 0; tile_y < tiles_per_col; ++tile_y) {
const int tile_y_offset = tile_y * max_tile_size;
const int this_tile_height =
(tile_y < tiles_per_col - 1) ? max_tile_size : height - tile_y_offset;
int tile_x;
if (tile_y > 0) {
memcpy(upper_row, current_tile_rows + (max_tile_size - 1) * width,
width * sizeof(*upper_row));
}
memcpy(current_tile_rows, &argb[tile_y_offset * width],
this_tile_height * width * sizeof(*current_tile_rows));
for (tile_x = 0; tile_x < tiles_per_row; ++tile_x) {
int pred;
int y;
const int tile_x_offset = tile_x * max_tile_size;
int all_x_max = tile_x_offset + max_tile_size;
if (all_x_max > width) {
all_x_max = width;
}
pred = GetBestPredictorForTile(width, height, tile_x, tile_y, bits,
(const int (*)[256])histo,
argb_scratch);
image[tile_y * tiles_per_row + tile_x] = 0xff000000u | (pred << 8);
CopyTileWithPrediction(width, height, tile_x, tile_y, bits, pred,
argb_scratch, argb);
for (y = 0; y < max_tile_size; ++y) {
int ix;
int all_x;
int all_y = tile_y_offset + y;
if (all_y >= height) {
break;
}
ix = all_y * width + tile_x_offset;
for (all_x = tile_x_offset; all_x < all_x_max; ++all_x, ++ix) {
UpdateHisto(histo, argb[ix]);
}
}
}
}
}
// Inverse prediction.
static void PredictorInverseTransform(const VP8LTransform* const transform,
int y_start, int y_end, uint32_t* data) {
const int width = transform->xsize_;
if (y_start == 0) { // First Row follows the L (mode=1) mode.
int x;
const uint32_t pred0 = Predictor0(data[-1], NULL);
AddPixelsEq(data, pred0);
for (x = 1; x < width; ++x) {
const uint32_t pred1 = Predictor1(data[x - 1], NULL);
AddPixelsEq(data + x, pred1);
}
data += width;
++y_start;
}
{
int y = y_start;
const int tile_width = 1 << transform->bits_;
const int mask = tile_width - 1;
const int safe_width = width & ~mask;
const int tiles_per_row = VP8LSubSampleSize(width, transform->bits_);
const uint32_t* pred_mode_base =
transform->data_ + (y >> transform->bits_) * tiles_per_row;
while (y < y_end) {
const uint32_t pred2 = Predictor2(data[-1], data - width);
const uint32_t* pred_mode_src = pred_mode_base;
VP8LPredictorFunc pred_func;
int x = 1;
int t = 1;
// First pixel follows the T (mode=2) mode.
AddPixelsEq(data, pred2);
// .. the rest:
while (x < safe_width) {
pred_func = VP8LPredictors[((*pred_mode_src++) >> 8) & 0xf];
for (; t < tile_width; ++t, ++x) {
const uint32_t pred = pred_func(data[x - 1], data + x - width);
AddPixelsEq(data + x, pred);
}
t = 0;
}
if (x < width) {
pred_func = VP8LPredictors[((*pred_mode_src++) >> 8) & 0xf];
for (; x < width; ++x) {
const uint32_t pred = pred_func(data[x - 1], data + x - width);
AddPixelsEq(data + x, pred);
}
}
data += width;
++y;
if ((y & mask) == 0) { // Use the same mask, since tiles are squares.
pred_mode_base += tiles_per_row;
}
}
}
}
void VP8LSubtractGreenFromBlueAndRed_C(uint32_t* argb_data, int num_pixels) {
int i;
for (i = 0; i < num_pixels; ++i) {
const uint32_t argb = argb_data[i];
const uint32_t green = (argb >> 8) & 0xff;
const uint32_t new_r = (((argb >> 16) & 0xff) - green) & 0xff;
const uint32_t new_b = ((argb & 0xff) - green) & 0xff;
argb_data[i] = (argb & 0xff00ff00) | (new_r << 16) | new_b;
}
}
// Add green to blue and red channels (i.e. perform the inverse transform of
// 'subtract green').
void VP8LAddGreenToBlueAndRed_C(uint32_t* data, int num_pixels) {
int i;
for (i = 0; i < num_pixels; ++i) {
const uint32_t argb = data[i];
const uint32_t green = ((argb >> 8) & 0xff);
uint32_t red_blue = (argb & 0x00ff00ffu);
red_blue += (green << 16) | green;
red_blue &= 0x00ff00ffu;
data[i] = (argb & 0xff00ff00u) | red_blue;
}
}
static WEBP_INLINE void MultipliersClear(VP8LMultipliers* const m) {
m->green_to_red_ = 0;
m->green_to_blue_ = 0;
m->red_to_blue_ = 0;
}
static WEBP_INLINE uint32_t ColorTransformDelta(int8_t color_pred,
int8_t color) {
return (uint32_t)((int)(color_pred) * color) >> 5;
}
static WEBP_INLINE void ColorCodeToMultipliers(uint32_t color_code,
VP8LMultipliers* const m) {
m->green_to_red_ = (color_code >> 0) & 0xff;
m->green_to_blue_ = (color_code >> 8) & 0xff;
m->red_to_blue_ = (color_code >> 16) & 0xff;
}
static WEBP_INLINE uint32_t MultipliersToColorCode(
const VP8LMultipliers* const m) {
return 0xff000000u |
((uint32_t)(m->red_to_blue_) << 16) |
((uint32_t)(m->green_to_blue_) << 8) |
m->green_to_red_;
}
void VP8LTransformColor_C(const VP8LMultipliers* const m, uint32_t* data,
int num_pixels) {
int i;
for (i = 0; i < num_pixels; ++i) {
const uint32_t argb = data[i];
const uint32_t green = argb >> 8;
const uint32_t red = argb >> 16;
uint32_t new_red = red;
uint32_t new_blue = argb;
new_red -= ColorTransformDelta(m->green_to_red_, green);
new_red &= 0xff;
new_blue -= ColorTransformDelta(m->green_to_blue_, green);
new_blue -= ColorTransformDelta(m->red_to_blue_, red);
new_blue &= 0xff;
data[i] = (argb & 0xff00ff00u) | (new_red << 16) | (new_blue);
}
}
void VP8LTransformColorInverse_C(const VP8LMultipliers* const m, uint32_t* data,
int num_pixels) {
int i;
for (i = 0; i < num_pixels; ++i) {
const uint32_t argb = data[i];
const uint32_t green = argb >> 8;
const uint32_t red = argb >> 16;
uint32_t new_red = red;
uint32_t new_blue = argb;
new_red += ColorTransformDelta(m->green_to_red_, green);
new_red &= 0xff;
new_blue += ColorTransformDelta(m->green_to_blue_, green);
new_blue += ColorTransformDelta(m->red_to_blue_, new_red);
new_blue &= 0xff;
data[i] = (argb & 0xff00ff00u) | (new_red << 16) | (new_blue);
}
}
static WEBP_INLINE uint8_t TransformColorRed(uint8_t green_to_red,
uint32_t argb) {
const uint32_t green = argb >> 8;
uint32_t new_red = argb >> 16;
new_red -= ColorTransformDelta(green_to_red, green);
return (new_red & 0xff);
}
static WEBP_INLINE uint8_t TransformColorBlue(uint8_t green_to_blue,
uint8_t red_to_blue,
uint32_t argb) {
const uint32_t green = argb >> 8;
const uint32_t red = argb >> 16;
uint8_t new_blue = argb;
new_blue -= ColorTransformDelta(green_to_blue, green);
new_blue -= ColorTransformDelta(red_to_blue, red);
return (new_blue & 0xff);
}
static float PredictionCostCrossColor(const int accumulated[256],
const int counts[256]) {
// Favor low entropy, locally and globally.
// Favor small absolute values for PredictionCostSpatial
static const double kExpValue = 2.4;
return CombinedShannonEntropy(counts, accumulated) +
PredictionCostSpatial(counts, 3, kExpValue);
}
static float GetPredictionCostCrossColorRed(
int tile_x_offset, int tile_y_offset, int all_x_max, int all_y_max,
int xsize, VP8LMultipliers prev_x, VP8LMultipliers prev_y, int green_to_red,
const int accumulated_red_histo[256], const uint32_t* const argb) {
int all_y;
int histo[256] = { 0 };
float cur_diff;
for (all_y = tile_y_offset; all_y < all_y_max; ++all_y) {
int ix = all_y * xsize + tile_x_offset;
int all_x;
for (all_x = tile_x_offset; all_x < all_x_max; ++all_x, ++ix) {
++histo[TransformColorRed(green_to_red, argb[ix])]; // red.
}
}
cur_diff = PredictionCostCrossColor(accumulated_red_histo, histo);
if ((uint8_t)green_to_red == prev_x.green_to_red_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if ((uint8_t)green_to_red == prev_y.green_to_red_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if (green_to_red == 0) {
cur_diff -= 3;
}
return cur_diff;
}
static void GetBestGreenToRed(
int tile_x_offset, int tile_y_offset, int all_x_max, int all_y_max,
int xsize, VP8LMultipliers prev_x, VP8LMultipliers prev_y,
const int accumulated_red_histo[256], const uint32_t* const argb,
VP8LMultipliers* const best_tx) {
int min_green_to_red = -64;
int max_green_to_red = 64;
int green_to_red = 0;
int eval_min = 1;
int eval_max = 1;
float cur_diff_min = MAX_DIFF_COST;
float cur_diff_max = MAX_DIFF_COST;
// Do a binary search to find the optimal green_to_red color transform.
while (max_green_to_red - min_green_to_red > 2) {
if (eval_min) {
cur_diff_min = GetPredictionCostCrossColorRed(
tile_x_offset, tile_y_offset, all_x_max, all_y_max, xsize,
prev_x, prev_y, min_green_to_red, accumulated_red_histo, argb);
eval_min = 0;
}
if (eval_max) {
cur_diff_max = GetPredictionCostCrossColorRed(
tile_x_offset, tile_y_offset, all_x_max, all_y_max, xsize,
prev_x, prev_y, max_green_to_red, accumulated_red_histo, argb);
eval_max = 0;
}
if (cur_diff_min < cur_diff_max) {
green_to_red = min_green_to_red;
max_green_to_red = (max_green_to_red + min_green_to_red) / 2;
eval_max = 1;
} else {
green_to_red = max_green_to_red;
min_green_to_red = (max_green_to_red + min_green_to_red) / 2;
eval_min = 1;
}
}
best_tx->green_to_red_ = green_to_red;
}
static float GetPredictionCostCrossColorBlue(
int tile_x_offset, int tile_y_offset, int all_x_max, int all_y_max,
int xsize, VP8LMultipliers prev_x, VP8LMultipliers prev_y,
int green_to_blue, int red_to_blue, const int accumulated_blue_histo[256],
const uint32_t* const argb) {
int all_y;
int histo[256] = { 0 };
float cur_diff;
for (all_y = tile_y_offset; all_y < all_y_max; ++all_y) {
int all_x;
int ix = all_y * xsize + tile_x_offset;
for (all_x = tile_x_offset; all_x < all_x_max; ++all_x, ++ix) {
++histo[TransformColorBlue(green_to_blue, red_to_blue, argb[ix])];
}
}
cur_diff = PredictionCostCrossColor(accumulated_blue_histo, histo);
if ((uint8_t)green_to_blue == prev_x.green_to_blue_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if ((uint8_t)green_to_blue == prev_y.green_to_blue_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if ((uint8_t)red_to_blue == prev_x.red_to_blue_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if ((uint8_t)red_to_blue == prev_y.red_to_blue_) {
cur_diff -= 3; // favor keeping the areas locally similar
}
if (green_to_blue == 0) {
cur_diff -= 3;
}
if (red_to_blue == 0) {
cur_diff -= 3;
}
return cur_diff;
}
static void GetBestGreenRedToBlue(
int tile_x_offset, int tile_y_offset, int all_x_max, int all_y_max,
int xsize, VP8LMultipliers prev_x, VP8LMultipliers prev_y, int quality,
const int accumulated_blue_histo[256], const uint32_t* const argb,
VP8LMultipliers* const best_tx) {
float best_diff = MAX_DIFF_COST;
float cur_diff;
const int step = (quality < 25) ? 32 : (quality > 50) ? 8 : 16;
const int min_green_to_blue = -32;
const int max_green_to_blue = 32;
const int min_red_to_blue = -32;
const int max_red_to_blue = 32;
const int num_iters =
(1 + (max_green_to_blue - min_green_to_blue) / step) *
(1 + (max_red_to_blue - min_red_to_blue) / step);
// Number of tries to get optimal green_to_blue & red_to_blue color transforms
// after finding a local minima.
const int max_tries_after_min = 4 + (num_iters >> 2);
int num_tries_after_min = 0;
int green_to_blue;
for (green_to_blue = min_green_to_blue;
green_to_blue <= max_green_to_blue &&
num_tries_after_min < max_tries_after_min;
green_to_blue += step) {
int red_to_blue;
for (red_to_blue = min_red_to_blue;
red_to_blue <= max_red_to_blue &&
num_tries_after_min < max_tries_after_min;
red_to_blue += step) {
cur_diff = GetPredictionCostCrossColorBlue(
tile_x_offset, tile_y_offset, all_x_max, all_y_max, xsize, prev_x,
prev_y, green_to_blue, red_to_blue, accumulated_blue_histo, argb);
if (cur_diff < best_diff) {
best_diff = cur_diff;
best_tx->green_to_blue_ = green_to_blue;
best_tx->red_to_blue_ = red_to_blue;
num_tries_after_min = 0;
} else {
++num_tries_after_min;
}
}
}
}
static VP8LMultipliers GetBestColorTransformForTile(
int tile_x, int tile_y, int bits,
VP8LMultipliers prev_x,
VP8LMultipliers prev_y,
int quality, int xsize, int ysize,
const int accumulated_red_histo[256],
const int accumulated_blue_histo[256],
const uint32_t* const argb) {
const int max_tile_size = 1 << bits;
const int tile_y_offset = tile_y * max_tile_size;
const int tile_x_offset = tile_x * max_tile_size;
const int all_x_max = GetMin(tile_x_offset + max_tile_size, xsize);
const int all_y_max = GetMin(tile_y_offset + max_tile_size, ysize);
VP8LMultipliers best_tx;
MultipliersClear(&best_tx);
GetBestGreenToRed(tile_x_offset, tile_y_offset, all_x_max, all_y_max, xsize,
prev_x, prev_y, accumulated_red_histo, argb, &best_tx);
GetBestGreenRedToBlue(tile_x_offset, tile_y_offset, all_x_max, all_y_max,
xsize, prev_x, prev_y, quality, accumulated_blue_histo,
argb, &best_tx);
return best_tx;
}
static void CopyTileWithColorTransform(int xsize, int ysize,
int tile_x, int tile_y,
int max_tile_size,
VP8LMultipliers color_transform,
uint32_t* argb) {
const int xscan = GetMin(max_tile_size, xsize - tile_x);
int yscan = GetMin(max_tile_size, ysize - tile_y);
argb += tile_y * xsize + tile_x;
while (yscan-- > 0) {
VP8LTransformColor(&color_transform, argb, xscan);
argb += xsize;
}
}
void VP8LColorSpaceTransform(int width, int height, int bits, int quality,
uint32_t* const argb, uint32_t* image) {
const int max_tile_size = 1 << bits;
const int tile_xsize = VP8LSubSampleSize(width, bits);
const int tile_ysize = VP8LSubSampleSize(height, bits);
int accumulated_red_histo[256] = { 0 };
int accumulated_blue_histo[256] = { 0 };
int tile_x, tile_y;
VP8LMultipliers prev_x, prev_y;
MultipliersClear(&prev_y);
MultipliersClear(&prev_x);
for (tile_y = 0; tile_y < tile_ysize; ++tile_y) {
for (tile_x = 0; tile_x < tile_xsize; ++tile_x) {
int y;
const int tile_x_offset = tile_x * max_tile_size;
const int tile_y_offset = tile_y * max_tile_size;
const int all_x_max = GetMin(tile_x_offset + max_tile_size, width);
const int all_y_max = GetMin(tile_y_offset + max_tile_size, height);
const int offset = tile_y * tile_xsize + tile_x;
if (tile_y != 0) {
ColorCodeToMultipliers(image[offset - tile_xsize], &prev_y);
}
prev_x = GetBestColorTransformForTile(tile_x, tile_y, bits,
prev_x, prev_y,
quality, width, height,
accumulated_red_histo,
accumulated_blue_histo,
argb);
image[offset] = MultipliersToColorCode(&prev_x);
CopyTileWithColorTransform(width, height, tile_x_offset, tile_y_offset,
max_tile_size, prev_x, argb);
// Gather accumulated histogram data.
for (y = tile_y_offset; y < all_y_max; ++y) {
int ix = y * width + tile_x_offset;
const int ix_end = ix + all_x_max - tile_x_offset;
for (; ix < ix_end; ++ix) {
const uint32_t pix = argb[ix];
if (ix >= 2 &&
pix == argb[ix - 2] &&
pix == argb[ix - 1]) {
continue; // repeated pixels are handled by backward references
}
if (ix >= width + 2 &&
argb[ix - 2] == argb[ix - width - 2] &&
argb[ix - 1] == argb[ix - width - 1] &&
pix == argb[ix - width]) {
continue; // repeated pixels are handled by backward references
}
++accumulated_red_histo[(pix >> 16) & 0xff];
++accumulated_blue_histo[(pix >> 0) & 0xff];
}
}
}
}
}
// Color space inverse transform.
static void ColorSpaceInverseTransform(const VP8LTransform* const transform,
int y_start, int y_end, uint32_t* data) {
const int width = transform->xsize_;
const int tile_width = 1 << transform->bits_;
const int mask = tile_width - 1;
const int safe_width = width & ~mask;
const int remaining_width = width - safe_width;
const int tiles_per_row = VP8LSubSampleSize(width, transform->bits_);
int y = y_start;
const uint32_t* pred_row =
transform->data_ + (y >> transform->bits_) * tiles_per_row;
while (y < y_end) {
const uint32_t* pred = pred_row;
VP8LMultipliers m = { 0, 0, 0 };
const uint32_t* const data_safe_end = data + safe_width;
const uint32_t* const data_end = data + width;
while (data < data_safe_end) {
ColorCodeToMultipliers(*pred++, &m);
VP8LTransformColorInverse(&m, data, tile_width);
data += tile_width;
}
if (data < data_end) { // Left-overs using C-version.
ColorCodeToMultipliers(*pred++, &m);
VP8LTransformColorInverse(&m, data, remaining_width);
data += remaining_width;
}
++y;
if ((y & mask) == 0) pred_row += tiles_per_row;
}
}
// Separate out pixels packed together using pixel-bundling.
// We define two methods for ARGB data (uint32_t) and alpha-only data (uint8_t).
#define COLOR_INDEX_INVERSE(FUNC_NAME, TYPE, GET_INDEX, GET_VALUE) \
void FUNC_NAME(const VP8LTransform* const transform, \
int y_start, int y_end, const TYPE* src, TYPE* dst) { \
int y; \
const int bits_per_pixel = 8 >> transform->bits_; \
const int width = transform->xsize_; \
const uint32_t* const color_map = transform->data_; \
if (bits_per_pixel < 8) { \
const int pixels_per_byte = 1 << transform->bits_; \
const int count_mask = pixels_per_byte - 1; \
const uint32_t bit_mask = (1 << bits_per_pixel) - 1; \
for (y = y_start; y < y_end; ++y) { \
uint32_t packed_pixels = 0; \
int x; \
for (x = 0; x < width; ++x) { \
/* We need to load fresh 'packed_pixels' once every */ \
/* 'pixels_per_byte' increments of x. Fortunately, pixels_per_byte */ \
/* is a power of 2, so can just use a mask for that, instead of */ \
/* decrementing a counter. */ \
if ((x & count_mask) == 0) packed_pixels = GET_INDEX(*src++); \
*dst++ = GET_VALUE(color_map[packed_pixels & bit_mask]); \
packed_pixels >>= bits_per_pixel; \
} \
} \
} else { \
for (y = y_start; y < y_end; ++y) { \
int x; \
for (x = 0; x < width; ++x) { \
*dst++ = GET_VALUE(color_map[GET_INDEX(*src++)]); \
} \
} \
} \
}
static WEBP_INLINE uint32_t GetARGBIndex(uint32_t idx) {
return (idx >> 8) & 0xff;
}
static WEBP_INLINE uint8_t GetAlphaIndex(uint8_t idx) {
return idx;
}
static WEBP_INLINE uint32_t GetARGBValue(uint32_t val) {
return val;
}
static WEBP_INLINE uint8_t GetAlphaValue(uint32_t val) {
return (val >> 8) & 0xff;
}
static COLOR_INDEX_INVERSE(ColorIndexInverseTransform, uint32_t, GetARGBIndex,
GetARGBValue)
COLOR_INDEX_INVERSE(VP8LColorIndexInverseTransformAlpha, uint8_t, GetAlphaIndex,
GetAlphaValue)
#undef COLOR_INDEX_INVERSE
void VP8LInverseTransform(const VP8LTransform* const transform,
int row_start, int row_end,
const uint32_t* const in, uint32_t* const out) {
const int width = transform->xsize_;
assert(row_start < row_end);
assert(row_end <= transform->ysize_);
switch (transform->type_) {
case SUBTRACT_GREEN:
VP8LAddGreenToBlueAndRed(out, (row_end - row_start) * width);
break;
case PREDICTOR_TRANSFORM:
PredictorInverseTransform(transform, row_start, row_end, out);
if (row_end != transform->ysize_) {
// The last predicted row in this iteration will be the top-pred row
// for the first row in next iteration.
memcpy(out - width, out + (row_end - row_start - 1) * width,
width * sizeof(*out));
}
break;
case CROSS_COLOR_TRANSFORM:
ColorSpaceInverseTransform(transform, row_start, row_end, out);
break;
case COLOR_INDEXING_TRANSFORM:
if (in == out && transform->bits_ > 0) {
// Move packed pixels to the end of unpacked region, so that unpacking
// can occur seamlessly.
// Also, note that this is the only transform that applies on
// the effective width of VP8LSubSampleSize(xsize_, bits_). All other
// transforms work on effective width of xsize_.
const int out_stride = (row_end - row_start) * width;
const int in_stride = (row_end - row_start) *
VP8LSubSampleSize(transform->xsize_, transform->bits_);
uint32_t* const src = out + out_stride - in_stride;
memmove(src, out, in_stride * sizeof(*src));
ColorIndexInverseTransform(transform, row_start, row_end, src, out);
} else {
ColorIndexInverseTransform(transform, row_start, row_end, in, out);
}
break;
}
}
//------------------------------------------------------------------------------
// Color space conversion.
static int is_big_endian(void) {
static const union {
uint16_t w;
uint8_t b[2];
} tmp = { 1 };
return (tmp.b[0] != 1);
}
void VP8LConvertBGRAToRGB_C(const uint32_t* src,
int num_pixels, uint8_t* dst) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
*dst++ = (argb >> 16) & 0xff;
*dst++ = (argb >> 8) & 0xff;
*dst++ = (argb >> 0) & 0xff;
}
}
void VP8LConvertBGRAToRGBA_C(const uint32_t* src,
int num_pixels, uint8_t* dst) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
*dst++ = (argb >> 16) & 0xff;
*dst++ = (argb >> 8) & 0xff;
*dst++ = (argb >> 0) & 0xff;
*dst++ = (argb >> 24) & 0xff;
}
}
void VP8LConvertBGRAToRGBA4444_C(const uint32_t* src,
int num_pixels, uint8_t* dst) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
const uint8_t rg = ((argb >> 16) & 0xf0) | ((argb >> 12) & 0xf);
const uint8_t ba = ((argb >> 0) & 0xf0) | ((argb >> 28) & 0xf);
#ifdef WEBP_SWAP_16BIT_CSP
*dst++ = ba;
*dst++ = rg;
#else
*dst++ = rg;
*dst++ = ba;
#endif
}
}
void VP8LConvertBGRAToRGB565_C(const uint32_t* src,
int num_pixels, uint8_t* dst) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
const uint8_t rg = ((argb >> 16) & 0xf8) | ((argb >> 13) & 0x7);
const uint8_t gb = ((argb >> 5) & 0xe0) | ((argb >> 3) & 0x1f);
#ifdef WEBP_SWAP_16BIT_CSP
*dst++ = gb;
*dst++ = rg;
#else
*dst++ = rg;
*dst++ = gb;
#endif
}
}
void VP8LConvertBGRAToBGR_C(const uint32_t* src,
int num_pixels, uint8_t* dst) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
*dst++ = (argb >> 0) & 0xff;
*dst++ = (argb >> 8) & 0xff;
*dst++ = (argb >> 16) & 0xff;
}
}
static void CopyOrSwap(const uint32_t* src, int num_pixels, uint8_t* dst,
int swap_on_big_endian) {
if (is_big_endian() == swap_on_big_endian) {
const uint32_t* const src_end = src + num_pixels;
while (src < src_end) {
const uint32_t argb = *src++;
#if !defined(WORDS_BIGENDIAN)
#if !defined(WEBP_REFERENCE_IMPLEMENTATION)
*(uint32_t*)dst = BSwap32(argb);
#else // WEBP_REFERENCE_IMPLEMENTATION
dst[0] = (argb >> 24) & 0xff;
dst[1] = (argb >> 16) & 0xff;
dst[2] = (argb >> 8) & 0xff;
dst[3] = (argb >> 0) & 0xff;
#endif
#else // WORDS_BIGENDIAN
dst[0] = (argb >> 0) & 0xff;
dst[1] = (argb >> 8) & 0xff;
dst[2] = (argb >> 16) & 0xff;
dst[3] = (argb >> 24) & 0xff;
#endif
dst += sizeof(argb);
}
} else {
memcpy(dst, src, num_pixels * sizeof(*src));
}
}
void VP8LConvertFromBGRA(const uint32_t* const in_data, int num_pixels,
WEBP_CSP_MODE out_colorspace, uint8_t* const rgba) {
switch (out_colorspace) {
case MODE_RGB:
VP8LConvertBGRAToRGB(in_data, num_pixels, rgba);
break;
case MODE_RGBA:
VP8LConvertBGRAToRGBA(in_data, num_pixels, rgba);
break;
case MODE_rgbA:
VP8LConvertBGRAToRGBA(in_data, num_pixels, rgba);
WebPApplyAlphaMultiply(rgba, 0, num_pixels, 1, 0);
break;
case MODE_BGR:
VP8LConvertBGRAToBGR(in_data, num_pixels, rgba);
break;
case MODE_BGRA:
CopyOrSwap(in_data, num_pixels, rgba, 1);
break;
case MODE_bgrA:
CopyOrSwap(in_data, num_pixels, rgba, 1);
WebPApplyAlphaMultiply(rgba, 0, num_pixels, 1, 0);
break;
case MODE_ARGB:
CopyOrSwap(in_data, num_pixels, rgba, 0);
break;
case MODE_Argb:
CopyOrSwap(in_data, num_pixels, rgba, 0);
WebPApplyAlphaMultiply(rgba, 1, num_pixels, 1, 0);
break;
case MODE_RGBA_4444:
VP8LConvertBGRAToRGBA4444(in_data, num_pixels, rgba);
break;
case MODE_rgbA_4444:
VP8LConvertBGRAToRGBA4444(in_data, num_pixels, rgba);
WebPApplyAlphaMultiply4444(rgba, num_pixels, 1, 0);
break;
case MODE_RGB_565:
VP8LConvertBGRAToRGB565(in_data, num_pixels, rgba);
break;
default:
assert(0); // Code flow should not reach here.
}
}
//------------------------------------------------------------------------------
// Bundles multiple (1, 2, 4 or 8) pixels into a single pixel.
void VP8LBundleColorMap(const uint8_t* const row, int width,
int xbits, uint32_t* const dst) {
int x;
if (xbits > 0) {
const int bit_depth = 1 << (3 - xbits);
const int mask = (1 << xbits) - 1;
uint32_t code = 0xff000000;
for (x = 0; x < width; ++x) {
const int xsub = x & mask;
if (xsub == 0) {
code = 0xff000000;
}
code |= row[x] << (8 + bit_depth * xsub);
dst[x >> xbits] = code;
}
} else {
for (x = 0; x < width; ++x) dst[x] = 0xff000000 | (row[x] << 8);
}
}
//------------------------------------------------------------------------------
static double ExtraCost(const uint32_t* population, int length) {
int i;
double cost = 0.;
for (i = 2; i < length - 2; ++i) cost += (i >> 1) * population[i + 2];
return cost;
}
static double ExtraCostCombined(const uint32_t* X, const uint32_t* Y,
int length) {
int i;
double cost = 0.;
for (i = 2; i < length - 2; ++i) {
const int xy = X[i + 2] + Y[i + 2];
cost += (i >> 1) * xy;
}
return cost;
}
// Returns the various RLE counts
static VP8LStreaks HuffmanCostCount(const uint32_t* population, int length) {
int i;
int streak = 0;
VP8LStreaks stats;
memset(&stats, 0, sizeof(stats));
for (i = 0; i < length - 1; ++i) {
++streak;
if (population[i] == population[i + 1]) {
continue;
}
stats.counts[population[i] != 0] += (streak > 3);
stats.streaks[population[i] != 0][(streak > 3)] += streak;
streak = 0;
}
++streak;
stats.counts[population[i] != 0] += (streak > 3);
stats.streaks[population[i] != 0][(streak > 3)] += streak;
return stats;
}
static VP8LStreaks HuffmanCostCombinedCount(const uint32_t* X,
const uint32_t* Y, int length) {
int i;
int streak = 0;
VP8LStreaks stats;
memset(&stats, 0, sizeof(stats));
for (i = 0; i < length - 1; ++i) {
const int xy = X[i] + Y[i];
const int xy_next = X[i + 1] + Y[i + 1];
++streak;
if (xy == xy_next) {
continue;
}
stats.counts[xy != 0] += (streak > 3);
stats.streaks[xy != 0][(streak > 3)] += streak;
streak = 0;
}
{
const int xy = X[i] + Y[i];
++streak;
stats.counts[xy != 0] += (streak > 3);
stats.streaks[xy != 0][(streak > 3)] += streak;
}
return stats;
}
//------------------------------------------------------------------------------
static void HistogramAdd(const VP8LHistogram* const a,
const VP8LHistogram* const b,
VP8LHistogram* const out) {
int i;
const int literal_size = VP8LHistogramNumCodes(a->palette_code_bits_);
assert(a->palette_code_bits_ == b->palette_code_bits_);
if (b != out) {
for (i = 0; i < literal_size; ++i) {
out->literal_[i] = a->literal_[i] + b->literal_[i];
}
for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
out->distance_[i] = a->distance_[i] + b->distance_[i];
}
for (i = 0; i < NUM_LITERAL_CODES; ++i) {
out->red_[i] = a->red_[i] + b->red_[i];
out->blue_[i] = a->blue_[i] + b->blue_[i];
out->alpha_[i] = a->alpha_[i] + b->alpha_[i];
}
} else {
for (i = 0; i < literal_size; ++i) {
out->literal_[i] += a->literal_[i];
}
for (i = 0; i < NUM_DISTANCE_CODES; ++i) {
out->distance_[i] += a->distance_[i];
}
for (i = 0; i < NUM_LITERAL_CODES; ++i) {
out->red_[i] += a->red_[i];
out->blue_[i] += a->blue_[i];
out->alpha_[i] += a->alpha_[i];
}
}
}
//------------------------------------------------------------------------------
VP8LProcessBlueAndRedFunc VP8LSubtractGreenFromBlueAndRed;
VP8LProcessBlueAndRedFunc VP8LAddGreenToBlueAndRed;
VP8LPredictorFunc VP8LPredictors[16];
VP8LTransformColorFunc VP8LTransformColor;
VP8LTransformColorFunc VP8LTransformColorInverse;
VP8LConvertFunc VP8LConvertBGRAToRGB;
VP8LConvertFunc VP8LConvertBGRAToRGBA;
VP8LConvertFunc VP8LConvertBGRAToRGBA4444;
VP8LConvertFunc VP8LConvertBGRAToRGB565;
VP8LConvertFunc VP8LConvertBGRAToBGR;
VP8LFastLog2SlowFunc VP8LFastLog2Slow;
VP8LFastLog2SlowFunc VP8LFastSLog2Slow;
VP8LCostFunc VP8LExtraCost;
VP8LCostCombinedFunc VP8LExtraCostCombined;
VP8LCostCountFunc VP8LHuffmanCostCount;
VP8LCostCombinedCountFunc VP8LHuffmanCostCombinedCount;
VP8LHistogramAddFunc VP8LHistogramAdd;
extern void VP8LDspInitSSE2(void);
extern void VP8LDspInitNEON(void);
extern void VP8LDspInitMIPS32(void);
void VP8LDspInit(void) {
memcpy(VP8LPredictors, kPredictorsC, sizeof(VP8LPredictors));
VP8LSubtractGreenFromBlueAndRed = VP8LSubtractGreenFromBlueAndRed_C;
VP8LAddGreenToBlueAndRed = VP8LAddGreenToBlueAndRed_C;
VP8LTransformColor = VP8LTransformColor_C;
VP8LTransformColorInverse = VP8LTransformColorInverse_C;
VP8LConvertBGRAToRGB = VP8LConvertBGRAToRGB_C;
VP8LConvertBGRAToRGBA = VP8LConvertBGRAToRGBA_C;
VP8LConvertBGRAToRGBA4444 = VP8LConvertBGRAToRGBA4444_C;
VP8LConvertBGRAToRGB565 = VP8LConvertBGRAToRGB565_C;
VP8LConvertBGRAToBGR = VP8LConvertBGRAToBGR_C;
VP8LFastLog2Slow = FastLog2Slow;
VP8LFastSLog2Slow = FastSLog2Slow;
VP8LExtraCost = ExtraCost;
VP8LExtraCostCombined = ExtraCostCombined;
VP8LHuffmanCostCount = HuffmanCostCount;
VP8LHuffmanCostCombinedCount = HuffmanCostCombinedCount;
VP8LHistogramAdd = HistogramAdd;
// If defined, use CPUInfo() to overwrite some pointers with faster versions.
if (VP8GetCPUInfo != NULL) {
#if defined(WEBP_USE_SSE2)
if (VP8GetCPUInfo(kSSE2)) {
VP8LDspInitSSE2();
}
#endif
#if defined(WEBP_USE_NEON)
if (VP8GetCPUInfo(kNEON)) {
VP8LDspInitNEON();
}
#endif
#if defined(WEBP_USE_MIPS32)
if (VP8GetCPUInfo(kMIPS32)) {
VP8LDspInitMIPS32();
}
#endif
}
}
//------------------------------------------------------------------------------
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