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