kc3-lang/brotli/enc/bit_cost.h

• Show log

  Commit

• Hash : 1447345c
  Author :
  Date : 2013-12-17T17:17:57
  

  Brotli format change: improved encoding of Huffman codes
  
  This change removes the redundant HCLEN, HLENINC and HLEN
  fields from the encoding of the complex Huffman codes and
  derives these from an invariant of the code length sequence.
  Based on a patch by Robert Obryk.
  

Download

• enc/bit_cost.h

• // Copyright 2013 Google Inc. All Rights Reserved.
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  // http://www.apache.org/licenses/LICENSE-2.0
  //
  // Unless required by applicable law or agreed to in writing, software
  // distributed under the License is distributed on an "AS IS" BASIS,
  // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  // See the License for the specific language governing permissions and
  // limitations under the License.
  //
  // Functions to estimate the bit cost of Huffman trees.
  
  #ifndef BROTLI_ENC_BIT_COST_H_
  #define BROTLI_ENC_BIT_COST_H_
  
  #include <stdint.h>
  
  #include "./entropy_encode.h"
  #include "./fast_log.h"
  
  namespace brotli {
  
  static const int kHuffmanExtraBits[kCodeLengthCodes] = {
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3,
  };
  
  static inline int HuffmanTreeBitCost(const int* counts, const uint8_t* depth) {
    int nbits = 0;
    for (int i = 0; i < kCodeLengthCodes; ++i) {
      nbits += counts[i] * (depth[i] + kHuffmanExtraBits[i]);
    }
    return nbits;
  }
  
  static inline int HuffmanTreeBitCost(
      const Histogram<kCodeLengthCodes>& histogram,
      const EntropyCode<kCodeLengthCodes>& entropy) {
    return HuffmanTreeBitCost(&histogram.data_[0], &entropy.depth_[0]);
  }
  
  static inline int HuffmanBitCost(const uint8_t* depth, int length) {
    int max_depth = 1;
    int histogram[kCodeLengthCodes] = { 0 };
    int tail_start = 0;
    // compute histogram of compacted huffman tree
    for (int i = 0; i < length;) {
      const int value = depth[i];
      if (value > max_depth) {
        max_depth = value;
      }
      int reps = 1;
      for (int k = i + 1; k < length && depth[k] == value; ++k) {
        ++reps;
      }
      i += reps;
      if (value == 0) {
        if (reps < 3) {
          histogram[0] += reps;
        } else {
          reps -= 3;
          while (reps >= 0) {
            ++histogram[17];
            reps >>= 3;
            --reps;
          }
        }
      } else {
        tail_start = i;
        ++histogram[value];
        --reps;
        if (reps < 3) {
          histogram[value] += reps;
        } else {
          reps -= 3;
          while (reps >= 0) {
            ++histogram[16];
            reps >>= 2;
            --reps;
          }
        }
      }
    }
  
    // create huffman tree of huffman tree
    uint8_t cost[kCodeLengthCodes] = { 0 };
    CreateHuffmanTree(histogram, kCodeLengthCodes, 7, cost);
    // account for rle extra bits
    cost[16] += 2;
    cost[17] += 3;
  
    int tree_size = 0;
    int bits = 6 + 3 * max_depth;  // huffman tree of huffman tree cost
    for (int i = 0; i < kCodeLengthCodes; ++i) {
      bits += histogram[i] * cost[i];  // huffman tree bit cost
      tree_size += histogram[i];
    }
    return bits;
  }
  
  template<int kSize>
  double PopulationCost(const Histogram<kSize>& histogram) {
    if (histogram.total_count_ == 0) {
      return 12;
    }
    int count = 0;
    for (int i = 0; i < kSize && count < 5; ++i) {
      if (histogram.data_[i] > 0) {
        ++count;
      }
    }
    if (count == 1) {
      return 12;
    }
    if (count == 2) {
      return 20 + histogram.total_count_;
    }
    uint8_t depth[kSize] = { 0 };
    CreateHuffmanTree(&histogram.data_[0], kSize, 15, depth);
    int bits = 0;
    for (int i = 0; i < kSize; ++i) {
      bits += histogram.data_[i] * depth[i];
    }
    if (count == 3) {
      bits += 28;
    } else if (count == 4) {
      bits += 37;
    } else {
      bits += HuffmanBitCost(depth, kSize);
    }
    return bits;
  }
  
  }  // namespace brotli
  
  #endif  // BROTLI_ENC_BIT_COST_H_
  

Download