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godot/drivers/webpold/dsp/lossless.c
Juan Linietsky da113fe40d -Upgraded webp to a MUCH newer version. Hoping it fixes some bugs in the process. Keeping old version just in case for now. 
-Added ability to convert xml and tscn scenes to binary on export, makes loading of larger scenes faster
2015-12-04 10:18:28 -03:00

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// 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)
#if defined(__cplusplus) || defined(c_plusplus)
extern "C" {
#endif
#include <math.h>
#include <stdlib.h>
#include "./lossless.h"
#include "../dec/vp8li.h"
#include "../dsp/yuv.h"
#include "../dsp/dsp.h"
#include "../enc/histogram.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
#define LOG_LOOKUP_IDX_MAX 256
static 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
};
float VP8LFastLog2(int v) {
if (v < LOG_LOOKUP_IDX_MAX) {
return kLog2Table[v];
} else if (v < APPROX_LOG_MAX) {
int log_cnt = 0;
while (v >= LOG_LOOKUP_IDX_MAX) {
++log_cnt;
v = v >> 1;
}
return kLog2Table[v] + (float)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));
}
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 pa = b - c;
const int pb = a - c;
return abs(pa) - abs(pb);
}
static WEBP_INLINE uint32_t Select(uint32_t a, uint32_t b, uint32_t c) {
const int pa_minus_pb =
Sub3((a >> 24) , (b >> 24) , (c >> 24) ) +
Sub3((a >> 16) & 0xff, (b >> 16) & 0xff, (c >> 16) & 0xff) +
Sub3((a >> 8) & 0xff, (b >> 8) & 0xff, (c >> 8) & 0xff) +
Sub3((a ) & 0xff, (b ) & 0xff, (c ) & 0xff);
return (pa_minus_pb <= 0) ? a : b;
}
//------------------------------------------------------------------------------
// Predictors
static uint32_t Predictor0(uint32_t left, const uint32_t* const top) {
(void)top;
(void)left;
return ARGB_BLACK;
}
static uint32_t Predictor1(uint32_t left, const uint32_t* const top) {
(void)top;
return left;
}
static uint32_t Predictor2(uint32_t left, const uint32_t* const top) {
(void)left;
return top[0];
}
static uint32_t Predictor3(uint32_t left, const uint32_t* const top) {
(void)left;
return top[1];
}
static uint32_t Predictor4(uint32_t left, const uint32_t* const top) {
(void)left;
return top[-1];
}
static uint32_t Predictor5(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average3(left, top[0], top[1]);
return pred;
}
static uint32_t Predictor6(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(left, top[-1]);
return pred;
}
static uint32_t Predictor7(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(left, top[0]);
return pred;
}
static uint32_t Predictor8(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(top[-1], top[0]);
(void)left;
return pred;
}
static uint32_t Predictor9(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average2(top[0], top[1]);
(void)left;
return pred;
}
static uint32_t Predictor10(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Average4(left, top[-1], top[0], top[1]);
return pred;
}
static uint32_t Predictor11(uint32_t left, const uint32_t* const top) {
const uint32_t pred = Select(top[0], left, top[-1]);
return pred;
}
static uint32_t Predictor12(uint32_t left, const uint32_t* const top) {
const uint32_t pred = ClampedAddSubtractFull(left, top[0], top[-1]);
return pred;
}
static uint32_t Predictor13(uint32_t left, const uint32_t* const top) {
const uint32_t pred = ClampedAddSubtractHalf(left, top[0], top[-1]);
return pred;
}
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 Shanon's entropy: Sum(p*log2(p))
static float ShannonEntropy(const int* const array, int n) {
int i;
float retval = 0.f;
int sum = 0;
for (i = 0; i < n; ++i) {
if (array[i] != 0) {
sum += array[i];
retval -= VP8LFastSLog2(array[i]);
}
}
retval += VP8LFastSLog2(sum);
return retval;
}
static float PredictionCostSpatialHistogram(int accumulated[4][256],
int tile[4][256]) {
int i;
int k;
int combo[256];
double retval = 0;
for (i = 0; i < 4; ++i) {
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
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