Overview

This is a useful reference to the whole area of source coding algorithms. This book 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 a useful reference tool. This book combines detailed description of algorithms and their implementation, plus accompanying pseudo-code that can be readily implemented on computer. It provides detailed pseudo-code presentation of over 30 algorithms, and an explanation of examples. Compression and throughput results are presented where appropriate, and serve as a validation of the assessments and recommendation made in the text. It also gives an in-depth coverage of the crucial areas of minimum-redundancy coding, arithmetic coding and adaptive coding.

Full Product Details

Author:   Alistair Moffat ,  Andrew Turpin
Publisher:   Springer
Imprint:   Springer
Edition:   2002 ed.
Volume:   669
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   1.300kg
ISBN:  

9780792376682

ISBN 10:   0792376684
Pages:   275
Publication Date:   31 March 2002
Audience:   Professional and scholarly ,  College/higher education ,  General/trade ,  Professional & Vocational ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 Data Compression Systems.- 1.1 Why compression?.- 1.2 Fundamental operations.- 1.3 Terminology.- 1.4 Related material.- 1.5 Analysis of algorithms.- 2 Fundamental Limits.- 2.1 Information content.- 2.2 Kraft inequality.- 2.3 Human compression.- 2.4 Mechanical compression systems.- 3 Static Codes.- 3.1  Unary and binary codes.- 3.2 Elias codes.- 3.3  Golomb and Rice codes.- 3.4 Interpolative coding.- 3.5 Making a choice.- 4 Minimum-Redundancy Coding.- 4.1  Shannon-Fano codes.- 4.2 Huffman coding.- 4.3  Canonical codes.- 4.4 Other decoding methods.- 4.5 Implementing Huffman’s algorithm.- 4.6 Natural probability distributions.- 4.7 Artificial probability distributions.- 4.8 Doing the housekeeping chores.- 4.9 Related material.- 5 Arithmetic Coding.- 5.1  Origins of arithmetic coding.- 5.2 Overview of arithmetic coding.- 5.3 Implementation of arithmetic coding.- 5.4 Variations.- 5.5 Binary arithmetic coding.- 5.6 Approximate arithmetic coding.- 5.7 Table-driven arithmetic coding.- 5.8 Related material.- 6 Adaptive Coding.- 6.1  Static and semi-static probability estimation.- 6.2 Adaptive probability estimation.- 6.3 Coping with novel symbols.- 6.4 Adaptive Huffman coding.- 6.5 Adaptive arithmetic coding.- 6.6 Maintaining cumulative statistics.- 6.7 Recency transformations.- 6.8 Splay tree coding.- 6.9 Structured arithmetic coding.- 6.10 Pseudo-adaptive coding.- 6.11 The Q-coder.- 6.12 Making a choice.- 7 Additional Constraints.- 7.1 Length-limited coding.- 7.2 Alphabetic coding.- 7.3 Alternative channel alphabets.- 7.4 Related material.- 8 Compression Systems.- 8.1  Sliding window compression.- 8.2 Prediction by partial matching.- 8.3 Burrows-Wheeler transform.- 8.4 Other compression systems.- 8.5 Lossy modeling.- 9 What Next?.- References.

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