Index: third_party/libwebp/utils/huffman_encode.c |
diff --git a/third_party/libwebp/utils/huffman_encode.c b/third_party/libwebp/utils/huffman_encode.c |
new file mode 100644 |
index 0000000000000000000000000000000000000000..8ccd291d22ad0991474370e49bbcadeb5b029325 |
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+++ b/third_party/libwebp/utils/huffman_encode.c |
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+// Copyright 2011 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/ |
+// ----------------------------------------------------------------------------- |
+// |
+// Author: Jyrki Alakuijala (jyrki@google.com) |
+// |
+// Entropy encoding (Huffman) for webp lossless. |
+ |
+#include <assert.h> |
+#include <stdlib.h> |
+#include <string.h> |
+#include "./huffman_encode.h" |
+#include "../utils/utils.h" |
+#include "../webp/format_constants.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 |
+// Hufmann tree compression, especially its RLE-part, give smaller output. |
+static int OptimizeHuffmanForRle(int length, int* const counts) { |
+ uint8_t* good_for_rle; |
+ // 1) Let's make the Huffman code more compatible with rle encoding. |
+ int i; |
+ for (; length >= 0; --length) { |
+ if (length == 0) { |
+ return 1; // 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. |
+ good_for_rle = (uint8_t*)calloc(length, 1); |
+ if (good_for_rle == NULL) { |
+ return 0; |
+ } |
+ { |
+ // 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. |
+ int 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. |
+ { |
+ int stride = 0; |
+ int limit = counts[0]; |
+ int 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)) { |
+ int k; |
+ // The stride must end, collapse what we have, if we have enough (4). |
+ int 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; |
+ } |
+ } |
+ } |
+ } |
+ free(good_for_rle); |
+ return 1; |
+} |
+ |
+typedef struct { |
+ int total_count_; |
+ int value_; |
+ int pool_index_left_; |
+ int pool_index_right_; |
+} HuffmanTree; |
+ |
+// 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 { |
+ if (t1->value_ < t2->value_) { |
+ return -1; |
+ } |
+ if (t1->value_ > t2->value_) { |
+ return 1; |
+ } |
+ return 0; |
+ } |
+} |
+ |
+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 int GenerateOptimalTree(const int* const histogram, int histogram_size, |
+ int tree_depth_limit, |
+ uint8_t* const bit_depths) { |
+ int count_min; |
+ HuffmanTree* tree_pool; |
+ HuffmanTree* tree; |
+ int tree_size_orig = 0; |
+ int i; |
+ |
+ for (i = 0; i < histogram_size; ++i) { |
+ if (histogram[i] != 0) { |
+ ++tree_size_orig; |
+ } |
+ } |
+ |
+ // 3 * tree_size is enough to cover all the nodes representing a |
+ // population and all the inserted nodes combining two existing nodes. |
+ // The tree pool needs 2 * (tree_size_orig - 1) entities, and the |
+ // tree needs exactly tree_size_orig entities. |
+ tree = (HuffmanTree*)WebPSafeMalloc(3ULL * tree_size_orig, sizeof(*tree)); |
+ if (tree == NULL) return 0; |
+ 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 int 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. |
+ int 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; |
+ } |
+ } |
+ } |
+ free(tree); |
+ return 1; |
+} |
+ |
+// ----------------------------------------------------------------------------- |
+// 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 |
+ |
+int VP8LCreateHuffmanTree(int* const histogram, int tree_depth_limit, |
+ HuffmanTreeCode* const tree) { |
+ const int num_symbols = tree->num_symbols; |
+ if (!OptimizeHuffmanForRle(num_symbols, histogram)) { |
+ return 0; |
+ } |
+ if (!GenerateOptimalTree(histogram, num_symbols, |
+ tree_depth_limit, tree->code_lengths)) { |
+ return 0; |
+ } |
+ // Create the actual bit codes for the bit lengths. |
+ ConvertBitDepthsToSymbols(tree); |
+ return 1; |
+} |