// Copyright 2012 Google Inc. All Rights Reserved. // // This code is licensed under the same terms as WebM: // Software License Agreement: http://www.webmproject.org/license/software/ // Additional IP Rights Grant: http://www.webmproject.org/license/additional/ // ----------------------------------------------------------------------------- // // 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" // Define the following if target arch is sure to have SSE2 // #define WEBP_TARGET_HAS_SSE2 #if defined(__cplusplus) || defined(c_plusplus) extern "C" { #endif #if defined(WEBP_TARGET_HAS_SSE2) #include #endif #include #include #include "./lossless.h" #include "../dec/vp8li.h" #include "./yuv.h" #define MAX_DIFF_COST (1e30f) // lookup table for small values of log2(int) #define APPROX_LOG_MAX 4096 #define LOG_2_RECIPROCAL 1.44269504088896338700465094007086 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 }; float VP8LFastSLog2Slow(int v) { assert(v >= LOG_LOOKUP_IDX_MAX); if (v < APPROX_LOG_MAX) { int log_cnt = 0; const float v_f = (float)v; while (v >= LOG_LOOKUP_IDX_MAX) { ++log_cnt; v = v >> 1; } return v_f * (kLog2Table[v] + log_cnt); } else { return (float)(LOG_2_RECIPROCAL * v * log((double)v)); } } float VP8LFastLog2Slow(int v) { assert(v >= LOG_LOOKUP_IDX_MAX); if (v < APPROX_LOG_MAX) { int log_cnt = 0; while (v >= LOG_LOOKUP_IDX_MAX) { ++log_cnt; v = v >> 1; } return kLog2Table[v] + log_cnt; } else { return (float)(LOG_2_RECIPROCAL * log((double)v)); } } //------------------------------------------------------------------------------ // Image transforms. // 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)); } #if defined(WEBP_TARGET_HAS_SSE2) static WEBP_INLINE uint32_t ClampedAddSubtractFull(uint32_t c0, uint32_t c1, uint32_t c2) { const __m128i zero = _mm_setzero_si128(); const __m128i C0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(c0), zero); const __m128i C1 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(c1), zero); const __m128i C2 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(c2), zero); const __m128i V1 = _mm_add_epi16(C0, C1); const __m128i V2 = _mm_sub_epi16(V1, C2); const __m128i b = _mm_packus_epi16(V2, V2); const uint32_t output = _mm_cvtsi128_si32(b); return output; } static WEBP_INLINE uint32_t ClampedAddSubtractHalf(uint32_t c0, uint32_t c1, uint32_t c2) { const uint32_t ave = Average2(c0, c1); const __m128i zero = _mm_setzero_si128(); const __m128i A0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(ave), zero); const __m128i B0 = _mm_unpacklo_epi8(_mm_cvtsi32_si128(c2), zero); const __m128i A1 = _mm_sub_epi16(A0, B0); const __m128i BgtA = _mm_cmpgt_epi16(B0, A0); const __m128i A2 = _mm_sub_epi16(A1, BgtA); const __m128i A3 = _mm_srai_epi16(A2, 1); const __m128i A4 = _mm_add_epi16(A0, A3); const __m128i A5 = _mm_packus_epi16(A4, A4); const uint32_t output = _mm_cvtsi128_si32(A5); return output; } static WEBP_INLINE uint32_t Select(uint32_t a, uint32_t b, uint32_t c) { int pa_minus_pb; const __m128i zero = _mm_setzero_si128(); const __m128i A0 = _mm_cvtsi32_si128(a); const __m128i B0 = _mm_cvtsi32_si128(b); const __m128i C0 = _mm_cvtsi32_si128(c); const __m128i AC0 = _mm_subs_epu8(A0, C0); const __m128i CA0 = _mm_subs_epu8(C0, A0); const __m128i BC0 = _mm_subs_epu8(B0, C0); const __m128i CB0 = _mm_subs_epu8(C0, B0); const __m128i AC = _mm_or_si128(AC0, CA0); const __m128i BC = _mm_or_si128(BC0, CB0); const __m128i pa = _mm_unpacklo_epi8(AC, zero); // |a - c| const __m128i pb = _mm_unpacklo_epi8(BC, zero); // |b - c| const __m128i diff = _mm_sub_epi16(pb, pa); { int16_t out[8]; _mm_storeu_si128((__m128i*)out, diff); pa_minus_pb = out[0] + out[1] + out[2] + out[3]; } return (pa_minus_pb <= 0) ? a : b; } #else 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 (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 (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; } #endif //------------------------------------------------------------------------------ // 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; } typedef uint32_t (*PredictorFunc)(uint32_t left, const uint32_t* const top); static const PredictorFunc kPredictors[16] = { Predictor0, Predictor1, Predictor2, Predictor3, Predictor4, Predictor5, Predictor6, Predictor7, Predictor8, Predictor9, Predictor10, Predictor11, Predictor12, Predictor13, Predictor0, Predictor0 // <- padding security sentinels }; // TODO(vikasa): Replace 256 etc with defines. static float PredictionCostSpatial(const int* counts, int weight_0, double exp_val) { const int significant_symbols = 16; 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* const X, const int* const Y, int n) { int i; double retval = 0.; int sumX = 0, sumXY = 0; for (i = 0; i < n; ++i) { const int x = X[i]; const int xy = X[i] + Y[i]; if (x != 0) { sumX += x; retval -= VP8LFastSLog2(x); } if (xy != 0) { sumXY += xy; retval -= VP8LFastSLog2(xy); } } retval += VP8LFastSLog2(sumX) + VP8LFastSLog2(sumXY); return (float)retval; } static float PredictionCostSpatialHistogram(int accumulated[4][256], 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], 256); } return (float)retval; } static int GetBestPredictorForTile(int width, int height, int tile_x, int tile_y, int bits, 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 ymax = (tile_size <= height - row_start) ? tile_size : height - row_start; const int xmax = (tile_size <= width - col_start) ? tile_size : width - col_start; int histo[4][256]; 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 PredictorFunc pred_func = kPredictors[mode]; float cur_diff; int y; memset(&histo[0][0], 0, sizeof(histo)); for (y = 0; y < ymax; ++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 < xmax; ++x) { const int col = col_start + x; uint32_t predict; uint32_t predict_diff; 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); } predict_diff = VP8LSubPixels(current_row[col], predict); ++histo[0][predict_diff >> 24]; ++histo[1][((predict_diff >> 16) & 0xff)]; ++histo[2][((predict_diff >> 8) & 0xff)]; ++histo[3][(predict_diff & 0xff)]; } } cur_diff = PredictionCostSpatialHistogram(accumulated, histo); 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 ymax = (tile_size <= height - row_start) ? tile_size : height - row_start; const int xmax = (tile_size <= width - col_start) ? tile_size : width - col_start; const PredictorFunc pred_func = kPredictors[mode]; const uint32_t* current_row = argb_scratch; int y; for (y = 0; y < ymax; ++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 < xmax; ++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, 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) { const uint32_t a = argb[ix]; ++histo[0][a >> 24]; ++histo[1][((a >> 16) & 0xff)]; ++histo[2][((a >> 8) & 0xff)]; ++histo[3][(a & 0xff)]; } } } } } // 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 mask = (1 << transform->bits_) - 1; 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) { int x; const uint32_t pred2 = Predictor2(data[-1], data - width); const uint32_t* pred_mode_src = pred_mode_base; PredictorFunc pred_func; // First pixel follows the T (mode=2) mode. AddPixelsEq(data, pred2); // .. the rest: pred_func = kPredictors[((*pred_mode_src++) >> 8) & 0xf]; for (x = 1; x < width; ++x) { uint32_t pred; if ((x & mask) == 0) { // start of tile. Read predictor function. pred_func = kPredictors[((*pred_mode_src++) >> 8) & 0xf]; } 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(uint32_t* argb_data, int num_pixs) { int i = 0; #if defined(WEBP_TARGET_HAS_SSE2) const __m128i mask = _mm_set1_epi32(0x0000ff00); for (; i + 4 < num_pixs; i += 4) { const __m128i in = _mm_loadu_si128((__m128i*)&argb_data[i]); const __m128i in_00g0 = _mm_and_si128(in, mask); // 00g0|00g0|... const __m128i in_0g00 = _mm_slli_epi32(in_00g0, 8); // 0g00|0g00|... const __m128i in_000g = _mm_srli_epi32(in_00g0, 8); // 000g|000g|... const __m128i in_0g0g = _mm_or_si128(in_0g00, in_000g); const __m128i out = _mm_sub_epi8(in, in_0g0g); _mm_storeu_si128((__m128i*)&argb_data[i], out); } // fallthrough and finish off with plain-C #endif for (; i < num_pixs; ++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'). static void AddGreenToBlueAndRed(const VP8LTransform* const transform, int y_start, int y_end, uint32_t* data) { const int width = transform->xsize_; const uint32_t* const data_end = data + (y_end - y_start) * width; #if defined(WEBP_TARGET_HAS_SSE2) const __m128i mask = _mm_set1_epi32(0x0000ff00); for (; data + 4 < data_end; data += 4) { const __m128i in = _mm_loadu_si128((__m128i*)data); const __m128i in_00g0 = _mm_and_si128(in, mask); // 00g0|00g0|... const __m128i in_0g00 = _mm_slli_epi32(in_00g0, 8); // 0g00|0g00|... const __m128i in_000g = _mm_srli_epi32(in_00g0, 8); // 000g|000g|... const __m128i in_0g0g = _mm_or_si128(in_0g00, in_000g); const __m128i out = _mm_add_epi8(in, in_0g0g); _mm_storeu_si128((__m128i*)data, out); } // fallthrough and finish off with plain-C #endif while (data < data_end) { const uint32_t argb = *data; const uint32_t green = ((argb >> 8) & 0xff); uint32_t red_blue = (argb & 0x00ff00ffu); red_blue += (green << 16) | green; red_blue &= 0x00ff00ffu; *data++ = (argb & 0xff00ff00u) | red_blue; } } typedef struct { // Note: the members are uint8_t, so that any negative values are // automatically converted to "mod 256" values. uint8_t green_to_red_; uint8_t green_to_blue_; uint8_t red_to_blue_; } Multipliers; static WEBP_INLINE void MultipliersClear(Multipliers* 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, Multipliers* 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(Multipliers* const m) { return 0xff000000u | ((uint32_t)(m->red_to_blue_) << 16) | ((uint32_t)(m->green_to_blue_) << 8) | m->green_to_red_; } static WEBP_INLINE uint32_t TransformColor(const Multipliers* const m, uint32_t argb, int inverse) { const uint32_t green = argb >> 8; const uint32_t red = argb >> 16; uint32_t new_red = red; uint32_t new_blue = argb; if (inverse) { 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; } else { 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; } return (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 WEBP_INLINE int SkipRepeatedPixels(const uint32_t* const argb, int ix, int xsize) { const uint32_t v = argb[ix]; if (ix >= xsize + 3) { if (v == argb[ix - xsize] && argb[ix - 1] == argb[ix - xsize - 1] && argb[ix - 2] == argb[ix - xsize - 2] && argb[ix - 3] == argb[ix - xsize - 3]) { return 1; } return v == argb[ix - 3] && v == argb[ix - 2] && v == argb[ix - 1]; } else if (ix >= 3) { return v == argb[ix - 3] && v == argb[ix - 2] && v == argb[ix - 1]; } return 0; } 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, 256) + PredictionCostSpatial(counts, 3, kExpValue); } static Multipliers GetBestColorTransformForTile( int tile_x, int tile_y, int bits, Multipliers prevX, Multipliers prevY, int step, int xsize, int ysize, int* accumulated_red_histo, int* accumulated_blue_histo, const uint32_t* const argb) { float best_diff = MAX_DIFF_COST; float cur_diff; const int halfstep = step / 2; 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; int green_to_red; int green_to_blue; int red_to_blue; int all_x_max = tile_x_offset + max_tile_size; int all_y_max = tile_y_offset + max_tile_size; Multipliers best_tx; MultipliersClear(&best_tx); if (all_x_max > xsize) { all_x_max = xsize; } if (all_y_max > ysize) { all_y_max = ysize; } for (green_to_red = -64; green_to_red <= 64; green_to_red += halfstep) { int histo[256] = { 0 }; int all_y; 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) { if (SkipRepeatedPixels(argb, ix, xsize)) { continue; } ++histo[TransformColorRed(green_to_red, argb[ix])]; // red. } } cur_diff = PredictionCostCrossColor(&accumulated_red_histo[0], &histo[0]); if ((uint8_t)green_to_red == prevX.green_to_red_) { cur_diff -= 3; // favor keeping the areas locally similar } if ((uint8_t)green_to_red == prevY.green_to_red_) { cur_diff -= 3; // favor keeping the areas locally similar } if (green_to_red == 0) { cur_diff -= 3; } if (cur_diff < best_diff) { best_diff = cur_diff; best_tx.green_to_red_ = green_to_red; } } best_diff = MAX_DIFF_COST; for (green_to_blue = -32; green_to_blue <= 32; green_to_blue += step) { for (red_to_blue = -32; red_to_blue <= 32; red_to_blue += step) { int all_y; int histo[256] = { 0 }; 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) { if (SkipRepeatedPixels(argb, ix, xsize)) { continue; } ++histo[TransformColorBlue(green_to_blue, red_to_blue, argb[ix])]; } } cur_diff = PredictionCostCrossColor(&accumulated_blue_histo[0], &histo[0]); if ((uint8_t)green_to_blue == prevX.green_to_blue_) { cur_diff -= 3; // favor keeping the areas locally similar } if ((uint8_t)green_to_blue == prevY.green_to_blue_) { cur_diff -= 3; // favor keeping the areas locally similar } if ((uint8_t)red_to_blue == prevX.red_to_blue_) { cur_diff -= 3; // favor keeping the areas locally similar } if ((uint8_t)red_to_blue == prevY.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; } 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; } } } return best_tx; } static void CopyTileWithColorTransform(int xsize, int ysize, int tile_x, int tile_y, int bits, Multipliers color_transform, uint32_t* const argb) { int y; int xscan = 1 << bits; int yscan = 1 << bits; tile_x <<= bits; tile_y <<= bits; if (xscan > xsize - tile_x) { xscan = xsize - tile_x; } if (yscan > ysize - tile_y) { yscan = ysize - tile_y; } yscan += tile_y; for (y = tile_y; y < yscan; ++y) { int ix = y * xsize + tile_x; const int end_ix = ix + xscan; for (; ix < end_ix; ++ix) { argb[ix] = TransformColor(&color_transform, argb[ix], 0); } } } void VP8LColorSpaceTransform(int width, int height, int bits, int step, uint32_t* const argb, uint32_t* image) { const int max_tile_size = 1 << bits; int tile_xsize = VP8LSubSampleSize(width, bits); int tile_ysize = VP8LSubSampleSize(height, bits); int accumulated_red_histo[256] = { 0 }; int accumulated_blue_histo[256] = { 0 }; int tile_y; int tile_x; Multipliers prevX; Multipliers prevY; MultipliersClear(&prevY); MultipliersClear(&prevX); for (tile_y = 0; tile_y < tile_ysize; ++tile_y) { for (tile_x = 0; tile_x < tile_xsize; ++tile_x) { Multipliers color_transform; int all_x_max; int y; const int tile_y_offset = tile_y * max_tile_size; const int tile_x_offset = tile_x * max_tile_size; if (tile_y != 0) { ColorCodeToMultipliers(image[tile_y * tile_xsize + tile_x - 1], &prevX); ColorCodeToMultipliers(image[(tile_y - 1) * tile_xsize + tile_x], &prevY); } else if (tile_x != 0) { ColorCodeToMultipliers(image[tile_y * tile_xsize + tile_x - 1], &prevX); } color_transform = GetBestColorTransformForTile(tile_x, tile_y, bits, prevX, prevY, step, width, height, &accumulated_red_histo[0], &accumulated_blue_histo[0], argb); image[tile_y * tile_xsize + tile_x] = MultipliersToColorCode(&color_transform); CopyTileWithColorTransform(width, height, tile_x, tile_y, bits, color_transform, argb); // Gather accumulated histogram data. all_x_max = tile_x_offset + max_tile_size; if (all_x_max > width) { all_x_max = width; } 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) { if (ix >= 2 && argb[ix] == argb[ix - 2] && argb[ix] == 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] && argb[ix] == argb[ix - width]) { continue; // repeated pixels are handled by backward references } ++accumulated_red_histo[(argb[ix] >> 16) & 0xff]; ++accumulated_blue_histo[argb[ix] & 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 mask = (1 << transform->bits_) - 1; 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; Multipliers m = { 0, 0, 0 }; int x; for (x = 0; x < width; ++x) { if ((x & mask) == 0) ColorCodeToMultipliers(*pred++, &m); data[x] = TransformColor(&m, data[x], 1); } data += width; ++y; if ((y & mask) == 0) pred_row += tiles_per_row;; } } // Separate out pixels packed together using pixel-bundling. static void ColorIndexInverseTransform( const VP8LTransform* const transform, int y_start, int y_end, const uint32_t* src, uint32_t* 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 = ((*src++) >> 8) & 0xff; *dst++ = 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++ = color_map[((*src++) >> 8) & 0xff]; } } } } void VP8LInverseTransform(const VP8LTransform* const transform, int row_start, int row_end, const uint32_t* const in, uint32_t* const out) { assert(row_start < row_end); assert(row_end <= transform->ysize_); switch (transform->type_) { case SUBTRACT_GREEN: AddGreenToBlueAndRed(transform, row_start, row_end, out); 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. const int width = transform->xsize_; 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) * transform->xsize_; 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); } static void ConvertBGRAToRGB(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; } } static void ConvertBGRAToRGBA(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; } } static void ConvertBGRAToRGBA4444(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 } } static void ConvertBGRAToRGB565(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 } } static void ConvertBGRAToBGR(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) { uint32_t argb = *src++; #if !defined(WEBP_REFERENCE_IMPLEMENTATION) #if !defined(__BIG_ENDIAN__) && (defined(__i386__) || defined(__x86_64__)) __asm__ volatile("bswap %0" : "=r"(argb) : "0"(argb)); *(uint32_t*)dst = argb; #elif !defined(__BIG_ENDIAN__) && defined(_MSC_VER) argb = _byteswap_ulong(argb); *(uint32_t*)dst = argb; #else dst[0] = (argb >> 24) & 0xff; dst[1] = (argb >> 16) & 0xff; dst[2] = (argb >> 8) & 0xff; dst[3] = (argb >> 0) & 0xff; #endif #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 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: ConvertBGRAToRGB(in_data, num_pixels, rgba); break; case MODE_RGBA: ConvertBGRAToRGBA(in_data, num_pixels, rgba); break; case MODE_rgbA: ConvertBGRAToRGBA(in_data, num_pixels, rgba); WebPApplyAlphaMultiply(rgba, 0, num_pixels, 1, 0); break; case MODE_BGR: ConvertBGRAToBGR(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: ConvertBGRAToRGBA4444(in_data, num_pixels, rgba); break; case MODE_rgbA_4444: ConvertBGRAToRGBA4444(in_data, num_pixels, rgba); WebPApplyAlphaMultiply4444(rgba, num_pixels, 1, 0); break; case MODE_RGB_565: ConvertBGRAToRGB565(in_data, num_pixels, rgba); break; default: assert(0); // Code flow should not reach here. } } //------------------------------------------------------------------------------ #if defined(__cplusplus) || defined(c_plusplus) } // extern "C" #endif