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// Copyright 2023 Google Inc. All Rights Reserved.
//
// Use of this source code is governed by a BSD-style license
// that can be found in the COPYING file in the root of the source
// tree. An additional intellectual property rights grant can be found
// in the file PATENTS. All contributing project authors may
// be found in the AUTHORS file in the root of the source tree.
// -----------------------------------------------------------------------------
//
// Utilities for palette analysis.
//
// Author: Vincent Rabaud (vrabaud@google.com)
#include "src/utils/palette.h"
#include <assert.h>
#include <stdlib.h>
#include "src/dsp/lossless_common.h"
#include "src/utils/color_cache_utils.h"
#include "src/utils/utils.h"
#include "src/webp/encode.h"
#include "src/webp/format_constants.h"
// -----------------------------------------------------------------------------
// Palette reordering for smaller sum of deltas (and for smaller storage).
static int PaletteCompareColorsForQsort(const void* p1, const void* p2) {
const uint32_t a = WebPMemToUint32((uint8_t*)p1);
const uint32_t b = WebPMemToUint32((uint8_t*)p2);
assert(a != b);
return (a < b) ? -1 : 1;
}
static WEBP_INLINE uint32_t PaletteComponentDistance(uint32_t v) {
return (v <= 128) ? v : (256 - v);
}
// Computes a value that is related to the entropy created by the
// palette entry diff.
//
// Note that the last & 0xff is a no-operation in the next statement, but
// removed by most compilers and is here only for regularity of the code.
static WEBP_INLINE uint32_t PaletteColorDistance(uint32_t col1, uint32_t col2) {
const uint32_t diff = VP8LSubPixels(col1, col2);
const int kMoreWeightForRGBThanForAlpha = 9;
uint32_t score;
score = PaletteComponentDistance((diff >> 0) & 0xff);
score += PaletteComponentDistance((diff >> 8) & 0xff);
score += PaletteComponentDistance((diff >> 16) & 0xff);
score *= kMoreWeightForRGBThanForAlpha;
score += PaletteComponentDistance((diff >> 24) & 0xff);
return score;
}
static WEBP_INLINE void SwapColor(uint32_t* const col1, uint32_t* const col2) {
const uint32_t tmp = *col1;
*col1 = *col2;
*col2 = tmp;
}
int SearchColorNoIdx(const uint32_t sorted[], uint32_t color, int num_colors) {
int low = 0, hi = num_colors;
if (sorted[low] == color) return low; // loop invariant: sorted[low] != color
while (1) {
const int mid = (low + hi) >> 1;
if (sorted[mid] == color) {
return mid;
} else if (sorted[mid] < color) {
low = mid;
} else {
hi = mid;
}
}
assert(0);
return 0;
}
void PrepareMapToPalette(const uint32_t palette[], uint32_t num_colors,
uint32_t sorted[], uint32_t idx_map[]) {
uint32_t i;
memcpy(sorted, palette, num_colors * sizeof(*sorted));
qsort(sorted, num_colors, sizeof(*sorted), PaletteCompareColorsForQsort);
for (i = 0; i < num_colors; ++i) {
idx_map[SearchColorNoIdx(sorted, palette[i], num_colors)] = i;
}
}
//------------------------------------------------------------------------------
#define COLOR_HASH_SIZE (MAX_PALETTE_SIZE * 4)
#define COLOR_HASH_RIGHT_SHIFT 22 // 32 - log2(COLOR_HASH_SIZE).
int GetColorPalette(const WebPPicture* const pic, uint32_t* const palette) {
int i;
int x, y;
int num_colors = 0;
uint8_t in_use[COLOR_HASH_SIZE] = {0};
uint32_t colors[COLOR_HASH_SIZE] = {0};
const uint32_t* argb = pic->argb;
const int width = pic->width;
const int height = pic->height;
uint32_t last_pix = ~argb[0]; // so we're sure that last_pix != argb[0]
assert(pic != NULL);
assert(pic->use_argb);
for (y = 0; y < height; ++y) {
for (x = 0; x < width; ++x) {
int key;
if (argb[x] == last_pix) {
continue;
}
last_pix = argb[x];
key = VP8LHashPix(last_pix, COLOR_HASH_RIGHT_SHIFT);
while (1) {
if (!in_use[key]) {
colors[key] = last_pix;
in_use[key] = 1;
++num_colors;
if (num_colors > MAX_PALETTE_SIZE) {
return MAX_PALETTE_SIZE + 1; // Exact count not needed.
}
break;
} else if (colors[key] == last_pix) {
break; // The color is already there.
} else {
// Some other color sits here, so do linear conflict resolution.
++key;
key &= (COLOR_HASH_SIZE - 1); // Key mask.
}
}
}
argb += pic->argb_stride;
}
if (palette != NULL) { // Fill the colors into palette.
num_colors = 0;
for (i = 0; i < COLOR_HASH_SIZE; ++i) {
if (in_use[i]) {
palette[num_colors] = colors[i];
++num_colors;
}
}
qsort(palette, num_colors, sizeof(*palette), PaletteCompareColorsForQsort);
}
return num_colors;
}
#undef COLOR_HASH_SIZE
#undef COLOR_HASH_RIGHT_SHIFT
// -----------------------------------------------------------------------------
// The palette has been sorted by alpha. This function checks if the other
// components of the palette have a monotonic development with regards to
// position in the palette. If all have monotonic development, there is
// no benefit to re-organize them greedily. A monotonic development
// would be spotted in green-only situations (like lossy alpha) or gray-scale
// images.
static int PaletteHasNonMonotonousDeltas(const uint32_t* const palette,
int num_colors) {
uint32_t predict = 0x000000;
int i;
uint8_t sign_found = 0x00;
for (i = 0; i < num_colors; ++i) {
const uint32_t diff = VP8LSubPixels(palette[i], predict);
const uint8_t rd = (diff >> 16) & 0xff;
const uint8_t gd = (diff >> 8) & 0xff;
const uint8_t bd = (diff >> 0) & 0xff;
if (rd != 0x00) {
sign_found |= (rd < 0x80) ? 1 : 2;
}
if (gd != 0x00) {
sign_found |= (gd < 0x80) ? 8 : 16;
}
if (bd != 0x00) {
sign_found |= (bd < 0x80) ? 64 : 128;
}
predict = palette[i];
}
return (sign_found & (sign_found << 1)) != 0; // two consequent signs.
}
static void PaletteSortMinimizeDeltas(const uint32_t* const palette_sorted,
int num_colors, uint32_t* const palette) {
uint32_t predict = 0x00000000;
int i, k;
memcpy(palette, palette_sorted, num_colors * sizeof(*palette));
if (!PaletteHasNonMonotonousDeltas(palette_sorted, num_colors)) return;
// Find greedily always the closest color of the predicted color to minimize
// deltas in the palette. This reduces storage needs since the
// palette is stored with delta encoding.
for (i = 0; i < num_colors; ++i) {
int best_ix = i;
uint32_t best_score = ~0U;
for (k = i; k < num_colors; ++k) {
const uint32_t cur_score = PaletteColorDistance(palette[k], predict);
if (best_score > cur_score) {
best_score = cur_score;
best_ix = k;
}
}
SwapColor(&palette[best_ix], &palette[i]);
predict = palette[i];
}
}
// -----------------------------------------------------------------------------
// Modified Zeng method from "A Survey on Palette Reordering
// Methods for Improving the Compression of Color-Indexed Images" by Armando J.
// Pinho and Antonio J. R. Neves.
// Finds the biggest cooccurrence in the matrix.
static void CoOccurrenceFindMax(const uint32_t* const cooccurrence,
uint32_t num_colors, uint8_t* const c1,
uint8_t* const c2) {
// Find the index that is most frequently located adjacent to other
// (different) indexes.
uint32_t best_sum = 0u;
uint32_t i, j, best_cooccurrence;
*c1 = 0u;
for (i = 0; i < num_colors; ++i) {
uint32_t sum = 0;
for (j = 0; j < num_colors; ++j) sum += cooccurrence[i * num_colors + j];
if (sum > best_sum) {
best_sum = sum;
*c1 = i;
}
}
// Find the index that is most frequently found adjacent to *c1.
*c2 = 0u;
best_cooccurrence = 0u;
for (i = 0; i < num_colors; ++i) {
if (cooccurrence[*c1 * num_colors + i] > best_cooccurrence) {
best_cooccurrence = cooccurrence[*c1 * num_colors + i];
*c2 = i;
}
}
assert(*c1 != *c2);
}
// Builds the cooccurrence matrix
static int CoOccurrenceBuild(const WebPPicture* const pic,
const uint32_t* const palette, uint32_t num_colors,
uint32_t* cooccurrence) {
uint32_t *lines, *line_top, *line_current, *line_tmp;
int x, y;
const uint32_t* src = pic->argb;
uint32_t prev_pix = ~src[0];
uint32_t prev_idx = 0u;
uint32_t idx_map[MAX_PALETTE_SIZE] = {0};
uint32_t palette_sorted[MAX_PALETTE_SIZE];
lines = (uint32_t*)WebPSafeMalloc(2 * pic->width, sizeof(*lines));
if (lines == NULL) {
return 0;
}
line_top = &lines[0];
line_current = &lines[pic->width];
PrepareMapToPalette(palette, num_colors, palette_sorted, idx_map);
for (y = 0; y < pic->height; ++y) {
for (x = 0; x < pic->width; ++x) {
const uint32_t pix = src[x];
if (pix != prev_pix) {
prev_idx = idx_map[SearchColorNoIdx(palette_sorted, pix, num_colors)];
prev_pix = pix;
}
line_current[x] = prev_idx;
// 4-connectivity is what works best as mentioned in "On the relation
// between Memon's and the modified Zeng's palette reordering methods".
if (x > 0 && prev_idx != line_current[x - 1]) {
const uint32_t left_idx = line_current[x - 1];
++cooccurrence[prev_idx * num_colors + left_idx];
++cooccurrence[left_idx * num_colors + prev_idx];
}
if (y > 0 && prev_idx != line_top[x]) {
const uint32_t top_idx = line_top[x];
++cooccurrence[prev_idx * num_colors + top_idx];
++cooccurrence[top_idx * num_colors + prev_idx];
}
}
line_tmp = line_top;
line_top = line_current;
line_current = line_tmp;
src += pic->argb_stride;
}
WebPSafeFree(lines);
return 1;
}
struct Sum {
uint8_t index;
uint32_t sum;
};
static int PaletteSortModifiedZeng(const WebPPicture* const pic,
const uint32_t* const palette_in,
uint32_t num_colors,
uint32_t* const palette) {
uint32_t i, j, ind;
uint8_t remapping[MAX_PALETTE_SIZE];
uint32_t* cooccurrence;
struct Sum sums[MAX_PALETTE_SIZE];
uint32_t first, last;
uint32_t num_sums;
// TODO(vrabaud) check whether one color images should use palette or not.
if (num_colors <= 1) return 1;
// Build the co-occurrence matrix.
cooccurrence =
(uint32_t*)WebPSafeCalloc(num_colors * num_colors, sizeof(*cooccurrence));
if (cooccurrence == NULL) {
return 0;
}
if (!CoOccurrenceBuild(pic, palette_in, num_colors, cooccurrence)) {
WebPSafeFree(cooccurrence);
return 0;
}
// Initialize the mapping list with the two best indices.
CoOccurrenceFindMax(cooccurrence, num_colors, &remapping[0], &remapping[1]);
// We need to append and prepend to the list of remapping. To this end, we
// actually define the next start/end of the list as indices in a vector (with
// a wrap around when the end is reached).
first = 0;
last = 1;
num_sums = num_colors - 2; // -2 because we know the first two values
if (num_sums > 0) {
// Initialize the sums with the first two remappings and find the best one
struct Sum* best_sum = &sums[0];
best_sum->index = 0u;
best_sum->sum = 0u;
for (i = 0, j = 0; i < num_colors; ++i) {
if (i == remapping[0] || i == remapping[1]) continue;
sums[j].index = i;
sums[j].sum = cooccurrence[i * num_colors + remapping[0]] +
cooccurrence[i * num_colors + remapping[1]];
if (sums[j].sum > best_sum->sum) best_sum = &sums[j];
++j;
}
while (num_sums > 0) {
const uint8_t best_index = best_sum->index;
// Compute delta to know if we need to prepend or append the best index.
int32_t delta = 0;
const int32_t n = num_colors - num_sums;
for (ind = first, j = 0; (ind + j) % num_colors != last + 1; ++j) {
const uint16_t l_j = remapping[(ind + j) % num_colors];
delta += (n - 1 - 2 * (int32_t)j) *
(int32_t)cooccurrence[best_index * num_colors + l_j];
}
if (delta > 0) {
first = (first == 0) ? num_colors - 1 : first - 1;
remapping[first] = best_index;
} else {
++last;
remapping[last] = best_index;
}
// Remove best_sum from sums.
*best_sum = sums[num_sums - 1];
--num_sums;
// Update all the sums and find the best one.
best_sum = &sums[0];
for (i = 0; i < num_sums; ++i) {
sums[i].sum += cooccurrence[best_index * num_colors + sums[i].index];
if (sums[i].sum > best_sum->sum) best_sum = &sums[i];
}
}
}
assert((last + 1) % num_colors == first);
WebPSafeFree(cooccurrence);
// Re-map the palette.
for (i = 0; i < num_colors; ++i) {
palette[i] = palette_in[remapping[(first + i) % num_colors]];
}
return 1;
}
// -----------------------------------------------------------------------------
int PaletteSort(PaletteSorting method, const struct WebPPicture* const pic,
const uint32_t* const palette_sorted, uint32_t num_colors,
uint32_t* const palette) {
switch (method) {
case kSortedDefault:
// Nothing to do, we have already sorted the palette.
memcpy(palette, palette_sorted, num_colors * sizeof(*palette));
return 1;
case kMinimizeDelta:
PaletteSortMinimizeDeltas(palette_sorted, num_colors, palette);
return 1;
case kModifiedZeng:
return PaletteSortModifiedZeng(pic, palette_sorted, num_colors, palette);
case kUnusedPalette:
case kPaletteSortingNum:
break;
}
assert(0);
return 0;
}