| // 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; |
| } |
| |
| static WEBP_INLINE int Sub3(int a, int b, int c) { |
| const int pb = b - c; |
| const int pa = a - c; |
| return abs(pb) - abs(pa); |
| } |
| |
| 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 |
| } |
| } |
| |
| //------------------------------------------------------------------------------ |
