55414bc573
Note that there are two Godot-specific changes made to libwebp
for the javascript/HTML5 platform. They are documented in the
README.md.
(cherry picked from commit ee3cf211c6)
417 lines
13 KiB
C
417 lines
13 KiB
C
// Copyright 2011 Google Inc. All Rights Reserved.
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//
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// Use of this source code is governed by a BSD-style license
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// that can be found in the COPYING file in the root of the source
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// tree. An additional intellectual property rights grant can be found
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// in the file PATENTS. All contributing project authors may
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// be found in the AUTHORS file in the root of the source tree.
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// -----------------------------------------------------------------------------
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//
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// Author: Jyrki Alakuijala (jyrki@google.com)
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//
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// Entropy encoding (Huffman) for webp lossless.
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#include <assert.h>
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#include <stdlib.h>
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#include <string.h>
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#include "./huffman_encode.h"
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#include "./utils.h"
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#include "../webp/format_constants.h"
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// -----------------------------------------------------------------------------
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// Util function to optimize the symbol map for RLE coding
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// Heuristics for selecting the stride ranges to collapse.
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static int ValuesShouldBeCollapsedToStrideAverage(int a, int b) {
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return abs(a - b) < 4;
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}
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// Change the population counts in a way that the consequent
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// Huffman tree compression, especially its RLE-part, give smaller output.
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static void OptimizeHuffmanForRle(int length, uint8_t* const good_for_rle,
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uint32_t* const counts) {
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// 1) Let's make the Huffman code more compatible with rle encoding.
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int i;
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for (; length >= 0; --length) {
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if (length == 0) {
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return; // All zeros.
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}
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if (counts[length - 1] != 0) {
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// Now counts[0..length - 1] does not have trailing zeros.
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break;
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}
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}
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// 2) Let's mark all population counts that already can be encoded
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// with an rle code.
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{
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// Let's not spoil any of the existing good rle codes.
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// Mark any seq of 0's that is longer as 5 as a good_for_rle.
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// Mark any seq of non-0's that is longer as 7 as a good_for_rle.
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uint32_t symbol = counts[0];
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int stride = 0;
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for (i = 0; i < length + 1; ++i) {
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if (i == length || counts[i] != symbol) {
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if ((symbol == 0 && stride >= 5) ||
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(symbol != 0 && stride >= 7)) {
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int k;
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for (k = 0; k < stride; ++k) {
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good_for_rle[i - k - 1] = 1;
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}
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}
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stride = 1;
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if (i != length) {
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symbol = counts[i];
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}
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} else {
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++stride;
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}
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}
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}
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// 3) Let's replace those population counts that lead to more rle codes.
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{
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uint32_t stride = 0;
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uint32_t limit = counts[0];
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uint32_t sum = 0;
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for (i = 0; i < length + 1; ++i) {
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if (i == length || good_for_rle[i] ||
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(i != 0 && good_for_rle[i - 1]) ||
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!ValuesShouldBeCollapsedToStrideAverage(counts[i], limit)) {
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if (stride >= 4 || (stride >= 3 && sum == 0)) {
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uint32_t k;
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// The stride must end, collapse what we have, if we have enough (4).
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uint32_t count = (sum + stride / 2) / stride;
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if (count < 1) {
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count = 1;
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}
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if (sum == 0) {
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// Don't make an all zeros stride to be upgraded to ones.
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count = 0;
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}
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for (k = 0; k < stride; ++k) {
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// We don't want to change value at counts[i],
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// that is already belonging to the next stride. Thus - 1.
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counts[i - k - 1] = count;
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}
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}
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stride = 0;
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sum = 0;
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if (i < length - 3) {
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// All interesting strides have a count of at least 4,
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// at least when non-zeros.
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limit = (counts[i] + counts[i + 1] +
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counts[i + 2] + counts[i + 3] + 2) / 4;
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} else if (i < length) {
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limit = counts[i];
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} else {
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limit = 0;
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}
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}
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++stride;
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if (i != length) {
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sum += counts[i];
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if (stride >= 4) {
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limit = (sum + stride / 2) / stride;
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}
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}
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}
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}
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}
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// A comparer function for two Huffman trees: sorts first by 'total count'
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// (more comes first), and then by 'value' (more comes first).
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static int CompareHuffmanTrees(const void* ptr1, const void* ptr2) {
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const HuffmanTree* const t1 = (const HuffmanTree*)ptr1;
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const HuffmanTree* const t2 = (const HuffmanTree*)ptr2;
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if (t1->total_count_ > t2->total_count_) {
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return -1;
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} else if (t1->total_count_ < t2->total_count_) {
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return 1;
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} else {
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assert(t1->value_ != t2->value_);
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return (t1->value_ < t2->value_) ? -1 : 1;
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}
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}
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static void SetBitDepths(const HuffmanTree* const tree,
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const HuffmanTree* const pool,
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uint8_t* const bit_depths, int level) {
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if (tree->pool_index_left_ >= 0) {
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SetBitDepths(&pool[tree->pool_index_left_], pool, bit_depths, level + 1);
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SetBitDepths(&pool[tree->pool_index_right_], pool, bit_depths, level + 1);
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} else {
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bit_depths[tree->value_] = level;
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}
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}
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// Create an optimal Huffman tree.
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//
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// (data,length): population counts.
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// tree_limit: maximum bit depth (inclusive) of the codes.
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// bit_depths[]: how many bits are used for the symbol.
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//
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// Returns 0 when an error has occurred.
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//
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// The catch here is that the tree cannot be arbitrarily deep
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//
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// count_limit is the value that is to be faked as the minimum value
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// and this minimum value is raised until the tree matches the
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// maximum length requirement.
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//
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// This algorithm is not of excellent performance for very long data blocks,
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// especially when population counts are longer than 2**tree_limit, but
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// we are not planning to use this with extremely long blocks.
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//
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// See http://en.wikipedia.org/wiki/Huffman_coding
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static void GenerateOptimalTree(const uint32_t* const histogram,
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int histogram_size,
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HuffmanTree* tree, int tree_depth_limit,
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uint8_t* const bit_depths) {
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uint32_t count_min;
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HuffmanTree* tree_pool;
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int tree_size_orig = 0;
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int i;
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for (i = 0; i < histogram_size; ++i) {
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if (histogram[i] != 0) {
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++tree_size_orig;
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}
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}
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if (tree_size_orig == 0) { // pretty optimal already!
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return;
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}
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tree_pool = tree + tree_size_orig;
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// For block sizes with less than 64k symbols we never need to do a
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// second iteration of this loop.
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// If we actually start running inside this loop a lot, we would perhaps
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// be better off with the Katajainen algorithm.
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assert(tree_size_orig <= (1 << (tree_depth_limit - 1)));
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for (count_min = 1; ; count_min *= 2) {
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int tree_size = tree_size_orig;
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// We need to pack the Huffman tree in tree_depth_limit bits.
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// So, we try by faking histogram entries to be at least 'count_min'.
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int idx = 0;
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int j;
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for (j = 0; j < histogram_size; ++j) {
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if (histogram[j] != 0) {
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const uint32_t count =
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(histogram[j] < count_min) ? count_min : histogram[j];
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tree[idx].total_count_ = count;
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tree[idx].value_ = j;
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tree[idx].pool_index_left_ = -1;
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tree[idx].pool_index_right_ = -1;
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++idx;
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}
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}
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// Build the Huffman tree.
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qsort(tree, tree_size, sizeof(*tree), CompareHuffmanTrees);
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if (tree_size > 1) { // Normal case.
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int tree_pool_size = 0;
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while (tree_size > 1) { // Finish when we have only one root.
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uint32_t count;
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tree_pool[tree_pool_size++] = tree[tree_size - 1];
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tree_pool[tree_pool_size++] = tree[tree_size - 2];
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count = tree_pool[tree_pool_size - 1].total_count_ +
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tree_pool[tree_pool_size - 2].total_count_;
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tree_size -= 2;
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{
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// Search for the insertion point.
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int k;
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for (k = 0; k < tree_size; ++k) {
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if (tree[k].total_count_ <= count) {
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break;
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}
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}
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memmove(tree + (k + 1), tree + k, (tree_size - k) * sizeof(*tree));
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tree[k].total_count_ = count;
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tree[k].value_ = -1;
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tree[k].pool_index_left_ = tree_pool_size - 1;
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tree[k].pool_index_right_ = tree_pool_size - 2;
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tree_size = tree_size + 1;
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}
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}
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SetBitDepths(&tree[0], tree_pool, bit_depths, 0);
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} else if (tree_size == 1) { // Trivial case: only one element.
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bit_depths[tree[0].value_] = 1;
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}
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{
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// Test if this Huffman tree satisfies our 'tree_depth_limit' criteria.
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int max_depth = bit_depths[0];
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for (j = 1; j < histogram_size; ++j) {
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if (max_depth < bit_depths[j]) {
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max_depth = bit_depths[j];
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}
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}
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if (max_depth <= tree_depth_limit) {
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break;
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}
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}
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}
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}
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// -----------------------------------------------------------------------------
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// Coding of the Huffman tree values
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static HuffmanTreeToken* CodeRepeatedValues(int repetitions,
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HuffmanTreeToken* tokens,
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int value, int prev_value) {
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assert(value <= MAX_ALLOWED_CODE_LENGTH);
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if (value != prev_value) {
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tokens->code = value;
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tokens->extra_bits = 0;
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++tokens;
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--repetitions;
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}
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while (repetitions >= 1) {
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if (repetitions < 3) {
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int i;
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for (i = 0; i < repetitions; ++i) {
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tokens->code = value;
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tokens->extra_bits = 0;
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++tokens;
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}
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break;
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} else if (repetitions < 7) {
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tokens->code = 16;
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tokens->extra_bits = repetitions - 3;
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++tokens;
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break;
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} else {
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tokens->code = 16;
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tokens->extra_bits = 3;
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++tokens;
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repetitions -= 6;
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}
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}
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return tokens;
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}
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static HuffmanTreeToken* CodeRepeatedZeros(int repetitions,
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HuffmanTreeToken* tokens) {
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while (repetitions >= 1) {
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if (repetitions < 3) {
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int i;
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for (i = 0; i < repetitions; ++i) {
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tokens->code = 0; // 0-value
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tokens->extra_bits = 0;
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++tokens;
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}
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break;
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} else if (repetitions < 11) {
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tokens->code = 17;
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tokens->extra_bits = repetitions - 3;
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++tokens;
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break;
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} else if (repetitions < 139) {
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tokens->code = 18;
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tokens->extra_bits = repetitions - 11;
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++tokens;
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break;
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} else {
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tokens->code = 18;
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tokens->extra_bits = 0x7f; // 138 repeated 0s
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++tokens;
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repetitions -= 138;
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}
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}
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return tokens;
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}
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int VP8LCreateCompressedHuffmanTree(const HuffmanTreeCode* const tree,
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HuffmanTreeToken* tokens, int max_tokens) {
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HuffmanTreeToken* const starting_token = tokens;
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HuffmanTreeToken* const ending_token = tokens + max_tokens;
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const int depth_size = tree->num_symbols;
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int prev_value = 8; // 8 is the initial value for rle.
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int i = 0;
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assert(tokens != NULL);
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while (i < depth_size) {
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const int value = tree->code_lengths[i];
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int k = i + 1;
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int runs;
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while (k < depth_size && tree->code_lengths[k] == value) ++k;
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runs = k - i;
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if (value == 0) {
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tokens = CodeRepeatedZeros(runs, tokens);
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} else {
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tokens = CodeRepeatedValues(runs, tokens, value, prev_value);
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prev_value = value;
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}
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i += runs;
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assert(tokens <= ending_token);
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}
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(void)ending_token; // suppress 'unused variable' warning
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return (int)(tokens - starting_token);
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}
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// -----------------------------------------------------------------------------
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// Pre-reversed 4-bit values.
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static const uint8_t kReversedBits[16] = {
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0x0, 0x8, 0x4, 0xc, 0x2, 0xa, 0x6, 0xe,
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0x1, 0x9, 0x5, 0xd, 0x3, 0xb, 0x7, 0xf
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};
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static uint32_t ReverseBits(int num_bits, uint32_t bits) {
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uint32_t retval = 0;
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int i = 0;
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while (i < num_bits) {
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i += 4;
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retval |= kReversedBits[bits & 0xf] << (MAX_ALLOWED_CODE_LENGTH + 1 - i);
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bits >>= 4;
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}
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retval >>= (MAX_ALLOWED_CODE_LENGTH + 1 - num_bits);
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return retval;
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}
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// Get the actual bit values for a tree of bit depths.
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static void ConvertBitDepthsToSymbols(HuffmanTreeCode* const tree) {
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// 0 bit-depth means that the symbol does not exist.
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int i;
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int len;
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uint32_t next_code[MAX_ALLOWED_CODE_LENGTH + 1];
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int depth_count[MAX_ALLOWED_CODE_LENGTH + 1] = { 0 };
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assert(tree != NULL);
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len = tree->num_symbols;
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for (i = 0; i < len; ++i) {
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const int code_length = tree->code_lengths[i];
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assert(code_length <= MAX_ALLOWED_CODE_LENGTH);
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++depth_count[code_length];
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}
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depth_count[0] = 0; // ignore unused symbol
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next_code[0] = 0;
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{
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uint32_t code = 0;
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for (i = 1; i <= MAX_ALLOWED_CODE_LENGTH; ++i) {
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code = (code + depth_count[i - 1]) << 1;
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next_code[i] = code;
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}
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}
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for (i = 0; i < len; ++i) {
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const int code_length = tree->code_lengths[i];
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tree->codes[i] = ReverseBits(code_length, next_code[code_length]++);
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}
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}
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// -----------------------------------------------------------------------------
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// Main entry point
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void VP8LCreateHuffmanTree(uint32_t* const histogram, int tree_depth_limit,
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uint8_t* const buf_rle,
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HuffmanTree* const huff_tree,
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HuffmanTreeCode* const huff_code) {
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const int num_symbols = huff_code->num_symbols;
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memset(buf_rle, 0, num_symbols * sizeof(*buf_rle));
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OptimizeHuffmanForRle(num_symbols, buf_rle, histogram);
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GenerateOptimalTree(histogram, num_symbols, huff_tree, tree_depth_limit,
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huff_code->code_lengths);
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// Create the actual bit codes for the bit lengths.
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ConvertBitDepthsToSymbols(huff_code);
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}
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