1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
|
// Copyright 2010 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.
//
// Entropy encoding (Huffman) utilities.
#ifndef BROTLI_ENC_ENTROPY_ENCODE_H_
#define BROTLI_ENC_ENTROPY_ENCODE_H_
#include <stdint.h>
#include <string.h>
#include "./histogram.h"
#include "./prefix.h"
namespace brotli {
// This function will create a Huffman tree.
//
// The (data,length) contains the population counts.
// The tree_limit is the maximum bit depth of the Huffman codes.
//
// The depth contains the tree, i.e., how many bits are used for
// the symbol.
//
// See http://en.wikipedia.org/wiki/Huffman_coding
void CreateHuffmanTree(const int *data,
const int length,
const int tree_limit,
uint8_t *depth);
// Change the population counts in a way that the consequent
// Hufmann tree compression, especially its rle-part will be more
// likely to compress this data more efficiently.
//
// length contains the size of the histogram.
// counts contains the population counts.
int OptimizeHuffmanCountsForRle(int length, int* counts);
// Write a huffman tree from bit depths into the bitstream representation
// of a Huffman tree. The generated Huffman tree is to be compressed once
// more using a Huffman tree
void WriteHuffmanTree(const uint8_t* depth, const int length,
uint8_t* tree,
uint8_t* extra_bits_data,
int* huffman_tree_size);
// Get the actual bit values for a tree of bit depths.
void ConvertBitDepthsToSymbols(const uint8_t *depth, int len, uint16_t *bits);
template<int kSize>
struct EntropyCode {
// How many bits for symbol.
uint8_t depth_[kSize];
// Actual bits used to represent the symbol.
uint16_t bits_[kSize];
// How many non-zero depth.
int count_;
// First four symbols with non-zero depth.
int symbols_[4];
};
template<int kSize>
void BuildEntropyCode(const Histogram<kSize>& histogram,
const int tree_limit,
const int alphabet_size,
EntropyCode<kSize>* code) {
memset(code->depth_, 0, sizeof(code->depth_));
memset(code->bits_, 0, sizeof(code->bits_));
memset(code->symbols_, 0, sizeof(code->symbols_));
code->count_ = 0;
if (histogram.total_count_ == 0) return;
for (int i = 0; i < kSize; ++i) {
if (histogram.data_[i] > 0) {
if (code->count_ < 4) code->symbols_[code->count_] = i;
++code->count_;
}
}
if (alphabet_size >= 50 && code->count_ >= 16) {
int counts[kSize];
memcpy(counts, &histogram.data_[0], sizeof(counts[0]) * kSize);
OptimizeHuffmanCountsForRle(alphabet_size, counts);
CreateHuffmanTree(counts, alphabet_size, tree_limit, &code->depth_[0]);
} else {
CreateHuffmanTree(&histogram.data_[0], alphabet_size, tree_limit,
&code->depth_[0]);
}
ConvertBitDepthsToSymbols(&code->depth_[0], alphabet_size, &code->bits_[0]);
}
static const int kCodeLengthCodes = 18;
// Literal entropy code.
typedef EntropyCode<256> EntropyCodeLiteral;
// Prefix entropy codes.
typedef EntropyCode<kNumCommandPrefixes> EntropyCodeCommand;
typedef EntropyCode<kNumDistancePrefixes> EntropyCodeDistance;
typedef EntropyCode<kNumBlockLenPrefixes> EntropyCodeBlockLength;
// Context map entropy code, 256 Huffman tree indexes + 16 run length codes.
typedef EntropyCode<272> EntropyCodeContextMap;
// Block type entropy code, 256 block types + 2 special symbols.
typedef EntropyCode<258> EntropyCodeBlockType;
} // namespace brotli
#endif // BROTLI_ENC_ENTROPY_ENCODE_H_
|
