Compression and Coding Algorithms

Couverture
Springer Science & Business Media, 31 mars 2002 - 275 pages
An authoritative reference to the whole area of source coding algorithms, Compression and Coding Algorithms will be a primary resource for both researchers and software engineers. The book also will be interest for people in broader area of design and analysis of algorithms and data structure. Practitioners, especially those who work in the software development and independent consulting industries creating compression software or other applications systems, in which compression plays a part, will benefit from techniques that are described.
Compression and Coding Algorithms describes in detail the coding mechanisms that are available for use in data compression systems. The well known Huffman coding technique is one mechanism, but there have been many others developed over the past few decades, and this book describes, explains and assesses them. People undertaking research of software development in the areas of compression and coding algorithms will find this book an indispensable reference. In particular, the careful and detailed description of algorithms and their implementation, plus accompanying pseudo-code that can be readily implemented on computer, make this book a definitive reference in an area currently without one.
The detailed pseudo-code presentation of over thirty algorithms, and careful explanation of examples, make this book approachable and authoritative. Compression and throughput results are presented where appropriate, and serve as a validation of the assessments and recommendation made in the text. The combination of implementation detail, thoughtful discussions, and careful presentation means that this book will occupy a pivotal role in this area for many years. In-depth coverage of the crucial areas of minimum-redundancy coding, arithmetic coding, adaptive coding make Compression and Coding Algorithms unique in its field.
 

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Table des matières

Data Compression Systems
1
12 Fundamental operations
3
13 Terminology
6
14 Related material
9
15 Analysis of algorithms
10
Fundamental Limits
15
22 Kraft inequality
17
23 Human compression
19
57 Tabledriven arithmetic coding
127
58 Related material
130
Adaptive Coding
131
62 Adaptive probability estimation
135
63 Coping with novel symbols
139
64 Adaptive Huffman coding
145
65 Adaptive arithmetic coding
154
66 Maintaining cumulative statistics
157

24 Mechanical compression systems
20
Static Codes
29
32 Elias codes
32
33 Golomb and Rice codes
36
34 Interpolative coding
42
35 Making a choice
48
MinimumRedundancy Coding
51
42 Huffman coding
53
43 Canonical codes
57
44 Other decoding methods
63
45 Implementing Huffmans algorithm
66
46 Natural probability distributions
70
47 Artificial probability distributions
78
48 Doing the housekeeping chores
81
49 Related material
88
Arithmetic Coding
91
51 Origins of arithmetic coding
92
53 Implementation of arithmetic coding
98
54 Variations
113
55 Binary arithmetic coding
118
56 Approximate arithmetic coding
122
67 Recency transformations
170
68 Splay tree coding
175
69 Structured arithmetic coding
177
610 Pseudoadaptive coding
179
611 The Qcoder
186
612 Making a choice
190
Additional Constraints
193
71 Lengthlimited coding
194
72 Alphabetic coding
202
73 Alternative channel alphabets
209
74 Related material
214
Compression Systems
215
82 Prediction by partial matching
221
83 BurrowsWheeler transform
232
84 Other compression systems
243
85 Lossy modeling
251
What Next?
253
Bibliography
257
Index
271
Droits d'auteur

Autres éditions - Tout afficher

Expressions et termes fréquents

Fréquemment cités

Page 257 - JG Cleary and IH Witten. Data compression using adaptive coding and partial string matching.
Page 260 - DA HUFFMAN. A method for the construction of minimum-redundancy codes.
Page 260 - Mathematics 25 (1973), pp. 83-94. 6. TC Hu and AC Tucker, Optimal computer search trees and variable length alphabetic codes, SIAM Journal of Applied Mathematics 21 (1971), pp.
Page 262 - JL Mitchell and WB Pennebaker "Software implementations of the Q-coder,
Page 262 - A. Moffat and L. Stuiver. Binary interpolative coding for effective index compression.
Page 262 - A. Moffat and R. Wan. RE-store: A system for compressing, browsing and searching large documents. In Proc.
Page 263 - Universal modeling and coding", IEEE Trans, on Information Theory IT-27, 1 (1981) 12-23.
Page 264 - ES Schwartz and B. Kallick. Generating a Canonical Prefix Encoding, Communications of the ACM, Vol.7, No.

Informations bibliographiques