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Diffstat (limited to 'media/libwebp/src/utils/palette.c')
| -rw-r--r-- | media/libwebp/src/utils/palette.c | 402 |
1 files changed, 402 insertions, 0 deletions
diff --git a/media/libwebp/src/utils/palette.c b/media/libwebp/src/utils/palette.c new file mode 100644 index 0000000000..515da21019 --- /dev/null +++ b/media/libwebp/src/utils/palette.c @@ -0,0 +1,402 @@ +// 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; +} |