441 lines
		
	
	
		
			14 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
			
		
		
	
	
			441 lines
		
	
	
		
			14 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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| 
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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/utils.h"
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| #include "../webp/format_constants.h"
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| 
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| // -----------------------------------------------------------------------------
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| // Util function to optimize the symbol map for RLE coding
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| 
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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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| 
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| // Change the population counts in a way that the consequent
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| // Hufmann tree compression, especially its RLE-part, give smaller output.
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| static int OptimizeHuffmanForRle(int length, int* const counts) {
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|   uint8_t* good_for_rle;
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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 1;  // 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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|   good_for_rle = (uint8_t*)calloc(length, 1);
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|   if (good_for_rle == NULL) {
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|     return 0;
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|   }
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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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|     int 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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|     int stride = 0;
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|     int limit = counts[0];
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|     int 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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|           int k;
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|           // The stride must end, collapse what we have, if we have enough (4).
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|           int 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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|   free(good_for_rle);
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|   return 1;
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| }
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| 
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| typedef struct {
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|   int total_count_;
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|   int value_;
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|   int pool_index_left_;
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|   int pool_index_right_;
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| } HuffmanTree;
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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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| 
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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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| 
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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 int GenerateOptimalTree(const int* const histogram, int histogram_size,
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|                                int tree_depth_limit,
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|                                uint8_t* const bit_depths) {
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|   int count_min;
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|   HuffmanTree* tree_pool;
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|   HuffmanTree* tree;
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|   int tree_size_orig = 0;
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|   int i;
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| 
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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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| 
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|   if (tree_size_orig == 0) {   // pretty optimal already!
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|     return 1;
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|   }
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| 
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|   // 3 * tree_size is enough to cover all the nodes representing a
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|   // population and all the inserted nodes combining two existing nodes.
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|   // The tree pool needs 2 * (tree_size_orig - 1) entities, and the
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|   // tree needs exactly tree_size_orig entities.
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|   tree = (HuffmanTree*)WebPSafeMalloc(3ULL * tree_size_orig, sizeof(*tree));
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|   if (tree == NULL) return 0;
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|   tree_pool = tree + tree_size_orig;
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| 
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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 int 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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| 
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|     // Build the Huffman tree.
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|     qsort(tree, tree_size, sizeof(*tree), CompareHuffmanTrees);
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| 
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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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|         int 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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| 
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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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|     {
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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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|   free(tree);
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|   return 1;
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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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| 
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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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| 
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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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| 
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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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| // -----------------------------------------------------------------------------
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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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| 
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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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| 
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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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| 
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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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| // -----------------------------------------------------------------------------
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| // Main entry point
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| 
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| int VP8LCreateHuffmanTree(int* const histogram, int tree_depth_limit,
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|                           HuffmanTreeCode* const tree) {
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|   const int num_symbols = tree->num_symbols;
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|   if (!OptimizeHuffmanForRle(num_symbols, histogram)) {
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|     return 0;
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|   }
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|   if (!GenerateOptimalTree(histogram, num_symbols,
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|                            tree_depth_limit, tree->code_lengths)) {
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|     return 0;
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|   }
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|   // Create the actual bit codes for the bit lengths.
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|   ConvertBitDepthsToSymbols(tree);
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|   return 1;
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| }
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