mirror of
https://github.com/opencv/opencv.git
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1139 lines
39 KiB
C
1139 lines
39 KiB
C
// Copyright 2012 Google Inc. All Rights Reserved.
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//
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// This code is licensed under the same terms as WebM:
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// Software License Agreement: http://www.webmproject.org/license/software/
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// Additional IP Rights Grant: http://www.webmproject.org/license/additional/
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// -----------------------------------------------------------------------------
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//
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// Image transforms and color space conversion methods for lossless decoder.
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//
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// Authors: Vikas Arora (vikaas.arora@gmail.com)
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// Jyrki Alakuijala (jyrki@google.com)
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// Urvang Joshi (urvang@google.com)
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#if defined(__cplusplus) || defined(c_plusplus)
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extern "C" {
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#endif
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#include <math.h>
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#include <stdlib.h>
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#include "./lossless.h"
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#include "../dec/vp8li.h"
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#include "../dsp/yuv.h"
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#include "../dsp/dsp.h"
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#include "../enc/histogram.h"
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#define MAX_DIFF_COST (1e30f)
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// lookup table for small values of log2(int)
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#define APPROX_LOG_MAX 4096
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#define LOG_2_RECIPROCAL 1.44269504088896338700465094007086
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#define LOG_LOOKUP_IDX_MAX 256
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static const float kLog2Table[LOG_LOOKUP_IDX_MAX] = {
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0.0000000000000000f, 0.0000000000000000f,
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1.0000000000000000f, 1.5849625007211560f,
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2.0000000000000000f, 2.3219280948873621f,
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2.5849625007211560f, 2.8073549220576041f,
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3.0000000000000000f, 3.1699250014423121f,
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3.3219280948873621f, 3.4594316186372973f,
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3.5849625007211560f, 3.7004397181410921f,
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3.8073549220576041f, 3.9068905956085187f,
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4.0000000000000000f, 4.0874628412503390f,
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4.1699250014423121f, 4.2479275134435852f,
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4.3219280948873626f, 4.3923174227787606f,
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4.4594316186372973f, 4.5235619560570130f,
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4.5849625007211560f, 4.6438561897747243f,
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4.7004397181410917f, 4.7548875021634682f,
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4.8073549220576037f, 4.8579809951275718f,
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4.9068905956085187f, 4.9541963103868749f,
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5.0000000000000000f, 5.0443941193584533f,
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5.0874628412503390f, 5.1292830169449663f,
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5.1699250014423121f, 5.2094533656289501f,
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5.2479275134435852f, 5.2854022188622487f,
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5.3219280948873626f, 5.3575520046180837f,
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5.3923174227787606f, 5.4262647547020979f,
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5.4594316186372973f, 5.4918530963296747f,
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5.5235619560570130f, 5.5545888516776376f,
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5.5849625007211560f, 5.6147098441152083f,
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5.6438561897747243f, 5.6724253419714951f,
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5.7004397181410917f, 5.7279204545631987f,
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5.7548875021634682f, 5.7813597135246599f,
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5.8073549220576037f, 5.8328900141647412f,
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5.8579809951275718f, 5.8826430493618415f,
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5.9068905956085187f, 5.9307373375628866f,
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5.9541963103868749f, 5.9772799234999167f,
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6.0000000000000000f, 6.0223678130284543f,
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6.0443941193584533f, 6.0660891904577720f,
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6.0874628412503390f, 6.1085244567781691f,
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6.1292830169449663f, 6.1497471195046822f,
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6.1699250014423121f, 6.1898245588800175f,
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6.2094533656289501f, 6.2288186904958804f,
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6.2479275134435852f, 6.2667865406949010f,
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6.2854022188622487f, 6.3037807481771030f,
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6.3219280948873626f, 6.3398500028846243f,
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6.3575520046180837f, 6.3750394313469245f,
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6.3923174227787606f, 6.4093909361377017f,
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6.4262647547020979f, 6.4429434958487279f,
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6.4594316186372973f, 6.4757334309663976f,
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6.4918530963296747f, 6.5077946401986963f,
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6.5235619560570130f, 6.5391588111080309f,
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6.5545888516776376f, 6.5698556083309478f,
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6.5849625007211560f, 6.5999128421871278f,
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6.6147098441152083f, 6.6293566200796094f,
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6.6438561897747243f, 6.6582114827517946f,
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6.6724253419714951f, 6.6865005271832185f,
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6.7004397181410917f, 6.7142455176661224f,
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6.7279204545631987f, 6.7414669864011464f,
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6.7548875021634682f, 6.7681843247769259f,
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6.7813597135246599f, 6.7944158663501061f,
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6.8073549220576037f, 6.8201789624151878f,
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6.8328900141647412f, 6.8454900509443747f,
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6.8579809951275718f, 6.8703647195834047f,
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6.8826430493618415f, 6.8948177633079437f,
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6.9068905956085187f, 6.9188632372745946f,
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6.9307373375628866f, 6.9425145053392398f,
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6.9541963103868749f, 6.9657842846620869f,
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6.9772799234999167f, 6.9886846867721654f,
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7.0000000000000000f, 7.0112272554232539f,
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7.0223678130284543f, 7.0334230015374501f,
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7.0443941193584533f, 7.0552824355011898f,
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7.0660891904577720f, 7.0768155970508308f,
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7.0874628412503390f, 7.0980320829605263f,
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7.1085244567781691f, 7.1189410727235076f,
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7.1292830169449663f, 7.1395513523987936f,
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7.1497471195046822f, 7.1598713367783890f,
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7.1699250014423121f, 7.1799090900149344f,
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7.1898245588800175f, 7.1996723448363644f,
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7.2094533656289501f, 7.2191685204621611f,
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7.2288186904958804f, 7.2384047393250785f,
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7.2479275134435852f, 7.2573878426926521f,
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7.2667865406949010f, 7.2761244052742375f,
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7.2854022188622487f, 7.2946207488916270f,
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7.3037807481771030f, 7.3128829552843557f,
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7.3219280948873626f, 7.3309168781146167f,
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7.3398500028846243f, 7.3487281542310771f,
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7.3575520046180837f, 7.3663222142458160f,
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7.3750394313469245f, 7.3837042924740519f,
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7.3923174227787606f, 7.4008794362821843f,
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7.4093909361377017f, 7.4178525148858982f,
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7.4262647547020979f, 7.4346282276367245f,
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7.4429434958487279f, 7.4512111118323289f,
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7.4594316186372973f, 7.4676055500829976f,
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7.4757334309663976f, 7.4838157772642563f,
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7.4918530963296747f, 7.4998458870832056f,
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7.5077946401986963f, 7.5156998382840427f,
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7.5235619560570130f, 7.5313814605163118f,
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7.5391588111080309f, 7.5468944598876364f,
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7.5545888516776376f, 7.5622424242210728f,
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7.5698556083309478f, 7.5774288280357486f,
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7.5849625007211560f, 7.5924570372680806f,
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7.5999128421871278f, 7.6073303137496104f,
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7.6147098441152083f, 7.6220518194563764f,
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7.6293566200796094f, 7.6366246205436487f,
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7.6438561897747243f, 7.6510516911789281f,
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7.6582114827517946f, 7.6653359171851764f,
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7.6724253419714951f, 7.6794800995054464f,
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7.6865005271832185f, 7.6934869574993252f,
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7.7004397181410917f, 7.7073591320808825f,
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7.7142455176661224f, 7.7210991887071855f,
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7.7279204545631987f, 7.7347096202258383f,
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7.7414669864011464f, 7.7481928495894605f,
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7.7548875021634682f, 7.7615512324444795f,
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7.7681843247769259f, 7.7747870596011736f,
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7.7813597135246599f, 7.7879025593914317f,
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7.7944158663501061f, 7.8008998999203047f,
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7.8073549220576037f, 7.8137811912170374f,
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7.8201789624151878f, 7.8265484872909150f,
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7.8328900141647412f, 7.8392037880969436f,
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7.8454900509443747f, 7.8517490414160571f,
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7.8579809951275718f, 7.8641861446542797f,
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7.8703647195834047f, 7.8765169465649993f,
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7.8826430493618415f, 7.8887432488982591f,
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7.8948177633079437f, 7.9008668079807486f,
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7.9068905956085187f, 7.9128893362299619f,
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7.9188632372745946f, 7.9248125036057812f,
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7.9307373375628866f, 7.9366379390025709f,
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7.9425145053392398f, 7.9483672315846778f,
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7.9541963103868749f, 7.9600019320680805f,
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7.9657842846620869f, 7.9715435539507719f,
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7.9772799234999167f, 7.9829935746943103f,
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7.9886846867721654f, 7.9943534368588577f
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};
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float VP8LFastLog2(int v) {
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if (v < LOG_LOOKUP_IDX_MAX) {
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return kLog2Table[v];
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} else if (v < APPROX_LOG_MAX) {
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int log_cnt = 0;
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while (v >= LOG_LOOKUP_IDX_MAX) {
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++log_cnt;
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v = v >> 1;
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}
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return kLog2Table[v] + (float)log_cnt;
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} else {
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return (float)(LOG_2_RECIPROCAL * log((double)v));
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}
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}
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//------------------------------------------------------------------------------
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// Image transforms.
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// In-place sum of each component with mod 256.
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static WEBP_INLINE void AddPixelsEq(uint32_t* a, uint32_t b) {
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const uint32_t alpha_and_green = (*a & 0xff00ff00u) + (b & 0xff00ff00u);
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const uint32_t red_and_blue = (*a & 0x00ff00ffu) + (b & 0x00ff00ffu);
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*a = (alpha_and_green & 0xff00ff00u) | (red_and_blue & 0x00ff00ffu);
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}
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static WEBP_INLINE uint32_t Average2(uint32_t a0, uint32_t a1) {
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return (((a0 ^ a1) & 0xfefefefeL) >> 1) + (a0 & a1);
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}
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static WEBP_INLINE uint32_t Average3(uint32_t a0, uint32_t a1, uint32_t a2) {
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return Average2(Average2(a0, a2), a1);
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}
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static WEBP_INLINE uint32_t Average4(uint32_t a0, uint32_t a1,
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uint32_t a2, uint32_t a3) {
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return Average2(Average2(a0, a1), Average2(a2, a3));
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}
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static WEBP_INLINE uint32_t Clip255(uint32_t a) {
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if (a < 256) {
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return a;
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}
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// return 0, when a is a negative integer.
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// return 255, when a is positive.
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return ~a >> 24;
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}
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static WEBP_INLINE int AddSubtractComponentFull(int a, int b, int c) {
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return Clip255(a + b - c);
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}
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static WEBP_INLINE uint32_t ClampedAddSubtractFull(uint32_t c0, uint32_t c1,
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uint32_t c2) {
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const int a = AddSubtractComponentFull(c0 >> 24, c1 >> 24, c2 >> 24);
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const int r = AddSubtractComponentFull((c0 >> 16) & 0xff,
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(c1 >> 16) & 0xff,
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(c2 >> 16) & 0xff);
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const int g = AddSubtractComponentFull((c0 >> 8) & 0xff,
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(c1 >> 8) & 0xff,
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(c2 >> 8) & 0xff);
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const int b = AddSubtractComponentFull(c0 & 0xff, c1 & 0xff, c2 & 0xff);
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return (a << 24) | (r << 16) | (g << 8) | b;
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}
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static WEBP_INLINE int AddSubtractComponentHalf(int a, int b) {
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return Clip255(a + (a - b) / 2);
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}
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static WEBP_INLINE uint32_t ClampedAddSubtractHalf(uint32_t c0, uint32_t c1,
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uint32_t c2) {
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const uint32_t ave = Average2(c0, c1);
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const int a = AddSubtractComponentHalf(ave >> 24, c2 >> 24);
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const int r = AddSubtractComponentHalf((ave >> 16) & 0xff, (c2 >> 16) & 0xff);
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const int g = AddSubtractComponentHalf((ave >> 8) & 0xff, (c2 >> 8) & 0xff);
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const int b = AddSubtractComponentHalf((ave >> 0) & 0xff, (c2 >> 0) & 0xff);
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return (a << 24) | (r << 16) | (g << 8) | b;
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}
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static WEBP_INLINE int Sub3(int a, int b, int c) {
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const int pa = b - c;
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const int pb = a - c;
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return abs(pa) - abs(pb);
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}
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static WEBP_INLINE uint32_t Select(uint32_t a, uint32_t b, uint32_t c) {
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const int pa_minus_pb =
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Sub3((a >> 24) , (b >> 24) , (c >> 24) ) +
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Sub3((a >> 16) & 0xff, (b >> 16) & 0xff, (c >> 16) & 0xff) +
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Sub3((a >> 8) & 0xff, (b >> 8) & 0xff, (c >> 8) & 0xff) +
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Sub3((a ) & 0xff, (b ) & 0xff, (c ) & 0xff);
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return (pa_minus_pb <= 0) ? a : b;
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}
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//------------------------------------------------------------------------------
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// Predictors
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static uint32_t Predictor0(uint32_t left, const uint32_t* const top) {
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(void)top;
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(void)left;
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return ARGB_BLACK;
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}
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static uint32_t Predictor1(uint32_t left, const uint32_t* const top) {
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(void)top;
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return left;
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}
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static uint32_t Predictor2(uint32_t left, const uint32_t* const top) {
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(void)left;
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return top[0];
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}
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static uint32_t Predictor3(uint32_t left, const uint32_t* const top) {
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(void)left;
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return top[1];
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}
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static uint32_t Predictor4(uint32_t left, const uint32_t* const top) {
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(void)left;
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return top[-1];
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}
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static uint32_t Predictor5(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average3(left, top[0], top[1]);
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return pred;
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}
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static uint32_t Predictor6(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average2(left, top[-1]);
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return pred;
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}
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static uint32_t Predictor7(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average2(left, top[0]);
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return pred;
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}
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static uint32_t Predictor8(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average2(top[-1], top[0]);
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(void)left;
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return pred;
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}
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static uint32_t Predictor9(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average2(top[0], top[1]);
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(void)left;
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return pred;
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}
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static uint32_t Predictor10(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Average4(left, top[-1], top[0], top[1]);
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return pred;
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}
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static uint32_t Predictor11(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = Select(top[0], left, top[-1]);
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return pred;
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}
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static uint32_t Predictor12(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = ClampedAddSubtractFull(left, top[0], top[-1]);
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return pred;
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}
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static uint32_t Predictor13(uint32_t left, const uint32_t* const top) {
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const uint32_t pred = ClampedAddSubtractHalf(left, top[0], top[-1]);
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return pred;
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}
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typedef uint32_t (*PredictorFunc)(uint32_t left, const uint32_t* const top);
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static const PredictorFunc kPredictors[16] = {
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Predictor0, Predictor1, Predictor2, Predictor3,
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Predictor4, Predictor5, Predictor6, Predictor7,
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Predictor8, Predictor9, Predictor10, Predictor11,
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Predictor12, Predictor13,
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Predictor0, Predictor0 // <- padding security sentinels
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};
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// TODO(vikasa): Replace 256 etc with defines.
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static float PredictionCostSpatial(const int* counts,
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int weight_0, double exp_val) {
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const int significant_symbols = 16;
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const double exp_decay_factor = 0.6;
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double bits = weight_0 * counts[0];
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int i;
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for (i = 1; i < significant_symbols; ++i) {
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bits += exp_val * (counts[i] + counts[256 - i]);
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exp_val *= exp_decay_factor;
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}
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return (float)(-0.1 * bits);
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}
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|
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// Compute the Shanon's entropy: Sum(p*log2(p))
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static float ShannonEntropy(const int* const array, int n) {
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int i;
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float retval = 0.f;
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int sum = 0;
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for (i = 0; i < n; ++i) {
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if (array[i] != 0) {
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sum += array[i];
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retval -= VP8LFastSLog2(array[i]);
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}
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}
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retval += VP8LFastSLog2(sum);
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return retval;
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}
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|
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static float PredictionCostSpatialHistogram(int accumulated[4][256],
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int tile[4][256]) {
|
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int i;
|
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int k;
|
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int combo[256];
|
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double retval = 0;
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for (i = 0; i < 4; ++i) {
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const double exp_val = 0.94;
|
|
retval += PredictionCostSpatial(&tile[i][0], 1, exp_val);
|
|
retval += ShannonEntropy(&tile[i][0], 256);
|
|
for (k = 0; k < 256; ++k) {
|
|
combo[k] = accumulated[i][k] + tile[i][k];
|
|
}
|
|
retval += ShannonEntropy(&combo[0], 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;
|
|
for (i = 0; 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;
|
|
while (data < data_end) {
|
|
const uint32_t argb = *data;
|
|
// "* 0001001u" is equivalent to "(green << 16) + green)"
|
|
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 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.
|
|
int i;
|
|
int combo[256];
|
|
for (i = 0; i < 256; ++i) {
|
|
combo[i] = accumulated[i] + counts[i];
|
|
}
|
|
return ShannonEntropy(combo, 256) +
|
|
ShannonEntropy(counts, 256) +
|
|
PredictionCostSpatial(counts, 3, 2.4); // Favor small absolute values.
|
|
}
|
|
|
|
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;
|
|
Multipliers tx;
|
|
MultipliersClear(&tx);
|
|
tx.green_to_red_ = green_to_red & 0xff;
|
|
|
|
for (all_y = tile_y_offset; all_y < all_y_max; ++all_y) {
|
|
uint32_t predict;
|
|
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;
|
|
}
|
|
predict = TransformColor(&tx, argb[ix], 0);
|
|
++histo[(predict >> 16) & 0xff]; // red.
|
|
}
|
|
}
|
|
cur_diff = PredictionCostCrossColor(&accumulated_red_histo[0], &histo[0]);
|
|
if (tx.green_to_red_ == prevX.green_to_red_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.green_to_red_ == prevY.green_to_red_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.green_to_red_ == 0) {
|
|
cur_diff -= 3;
|
|
}
|
|
if (cur_diff < best_diff) {
|
|
best_diff = cur_diff;
|
|
best_tx = tx;
|
|
}
|
|
}
|
|
best_diff = MAX_DIFF_COST;
|
|
green_to_red = best_tx.green_to_red_;
|
|
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 };
|
|
Multipliers tx;
|
|
tx.green_to_red_ = green_to_red;
|
|
tx.green_to_blue_ = green_to_blue;
|
|
tx.red_to_blue_ = red_to_blue;
|
|
for (all_y = tile_y_offset; all_y < all_y_max; ++all_y) {
|
|
uint32_t predict;
|
|
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;
|
|
}
|
|
predict = TransformColor(&tx, argb[ix], 0);
|
|
++histo[predict & 0xff]; // blue.
|
|
}
|
|
}
|
|
cur_diff =
|
|
PredictionCostCrossColor(&accumulated_blue_histo[0], &histo[0]);
|
|
if (tx.green_to_blue_ == prevX.green_to_blue_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.green_to_blue_ == prevY.green_to_blue_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.red_to_blue_ == prevX.red_to_blue_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.red_to_blue_ == prevY.red_to_blue_) {
|
|
cur_diff -= 3; // favor keeping the areas locally similar
|
|
}
|
|
if (tx.green_to_blue_ == 0) {
|
|
cur_diff -= 3;
|
|
}
|
|
if (tx.red_to_blue_ == 0) {
|
|
cur_diff -= 3;
|
|
}
|
|
if (cur_diff < best_diff) {
|
|
best_diff = cur_diff;
|
|
best_tx = tx;
|
|
}
|
|
}
|
|
}
|
|
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++;
|
|
*dst++ = ((argb >> 16) & 0xf0) | ((argb >> 12) & 0xf);
|
|
*dst++ = ((argb >> 0) & 0xf0) | ((argb >> 28) & 0xf);
|
|
}
|
|
}
|
|
|
|
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++;
|
|
*dst++ = ((argb >> 16) & 0xf8) | ((argb >> 13) & 0x7);
|
|
*dst++ = ((argb >> 5) & 0xe0) | ((argb >> 3) & 0x1f);
|
|
}
|
|
}
|
|
|
|
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(__BIG_ENDIAN__) && (defined(__i386__) || defined(__x86_64__))
|
|
__asm__ volatile("bswap %0" : "=r"(argb) : "0"(argb));
|
|
*(uint32_t*)dst = argb;
|
|
dst += sizeof(argb);
|
|
#elif !defined(__BIG_ENDIAN__) && defined(_MSC_VER)
|
|
argb = _byteswap_ulong(argb);
|
|
*(uint32_t*)dst = argb;
|
|
dst += sizeof(argb);
|
|
#else
|
|
*dst++ = (argb >> 24) & 0xff;
|
|
*dst++ = (argb >> 16) & 0xff;
|
|
*dst++ = (argb >> 8) & 0xff;
|
|
*dst++ = (argb >> 0) & 0xff;
|
|
#endif
|
|
}
|
|
} 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
|