Compression and Coding Algorithms
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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Data Compression Systems
12 Fundamental operations
14 Related material
15 Analysis of algorithms
22 Kraft inequality
23 Human compression
57 Tabledriven arithmetic coding
58 Related material
62 Adaptive probability estimation
63 Coping with novel symbols
64 Adaptive Huffman coding
65 Adaptive arithmetic coding
66 Maintaining cumulative statistics
24 Mechanical compression systems
32 Elias codes
33 Golomb and Rice codes
34 Interpolative coding
35 Making a choice
42 Huffman coding
43 Canonical codes
44 Other decoding methods
45 Implementing Huffmans algorithm
46 Natural probability distributions
47 Artificial probability distributions
48 Doing the housekeeping chores
49 Related material
51 Origins of arithmetic coding
53 Implementation of arithmetic coding
55 Binary arithmetic coding
56 Approximate arithmetic coding
67 Recency transformations
68 Splay tree coding
69 Structured arithmetic coding
610 Pseudoadaptive coding
611 The Qcoder
612 Making a choice
71 Lengthlimited coding
72 Alphabetic coding
73 Alternative channel alphabets
74 Related material
82 Prediction by partial matching
83 BurrowsWheeler transform
84 Other compression systems
85 Lossy modeling
Autres éditions - Tout afficher
adaptive Huffman coding approximate arithmetic coding array ASCII assigned assumed bigrams binary code bits per symbol block bucket Burrows-Wheeler transform byte BZIP2 calculated canonical code channel alphabet Chapter coder codeword lengths coding methods compression effectiveness compression loss compression system computation context corresponding cost cum-prob data compression data structure described encoder and decoder entropy example Fenwick tree Figure frequency counts function Golomb code Huffman tree Huffman's algorithm implementation increment input integer interpolative code Iog2 log2 loop mechanism minimal binary code minimum-redundancy code Moffat nmax number of bits number of symbols operations output package pair permuted pointers possible prefix prefix code prelude probability distribution probability estimation queue renormalization represent Rice codes Section self-information self-probabilities semi-static sequence sibling list sorted source alphabet splay tree step stored string subalphabet symbol frequencies symbol number symbol probabilities Table techniques transmitted unary weight Witten words zero zero-order
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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.
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