Introduction to Data Compression

Introduction to Data Compression

4th Edition - October 4, 2012

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  • Author: Khalid Sayood
  • eBook ISBN: 9780124160002

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Introduction to Data Compression, Fourth Edition, is a concise and comprehensive guide to the art and science of data compression. This new edition includes all the cutting edge updates the reader will need during the work day and in class. It provides an extensive introduction to the theory underlying today’s compression techniques with detailed instruction for their applications using several examples to explain the concepts.Encompassing the entire field of data compression, this book covers lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. New to this fourth edition is a more detailed description of the JPEG 2000 standard as well as speech coding for internet applications. A source code is also provided via a companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications.This text will appeal to professionals, software and hardware engineers, students, and anyone interested in digital libraries and multimedia.

Key Features

  • New content added to include a more detailed description of the JPEG 2000 standard
  • New content includes speech coding for internet applications
  • Explains established and emerging standards in depth including JPEG 2000, JPEG-LS, MPEG-2, H.264, JBIG 2, ADPCM, LPC, CELP, MELP, and iLBC
  • Source code provided via companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications


Professionals, software and hardware engineers, students; digital libraries, multimedia

Table of Contents

  • Editor Board



    1 Audience

    2 Course Use

    3 Approach

    4 Learning from This Book

    5 Content and Organization

    6 A Personal View



    1.1 Compression Techniques

    1.2 Modeling and Coding

    1.3 Summary

    1.4 Projects and Problems


    Mathematical Preliminaries for Lossless Compression

    2.1 Overview

    2.2 A Brief Introduction to Information Theory

    2.3 Models

    2.4 Coding

    2.5 Algorithmic Information Theory

    2.6 Minimum Description Length Principle

    2.7 Summary

    2.8 Projects and Problems


    Huffman Coding

    3.1 Overview

    3.2 The Huffman Coding Algorithm

    3.3 Nonbinary Huffman Codes

    3.4 Adaptive Huffman Coding

    3.5 Golomb Codes

    3.6 Rice Codes

    3.7 Tunstall Codes

    3.8 Applications of Huffman Coding

    3.9 Summary

    Further Reading

    3.10 Projects and Problems


    Arithmetic Coding

    4.1 Overview

    4.2 Introduction

    4.3 Coding a Sequence

    4.4 Generating a Binary Code

    4.5 Adaptive Arithmetic Coding

    4.6 Binary Arithmetic Coding

    4.7 Comparison of Huffman and Arithmetic Coding

    4.8 Applications

    4.9 Summary

    4.10 Projects and Problems


    Dictionary Techniques

    5.1 Overview

    5.2 Introduction

    5.3 Static Dictionary

    5.4 Adaptive Dictionary

    5.5 Applications

    5.6 Beyond Compression—Lempel-Ziv Complexity

    5.7 Summary

    5.8 Projects and Problems


    Context-Based Compression

    6.1 Overview

    6.2 Introduction

    6.3 Prediction with Partial Match (ppm)

    6.4 The Burrows-Wheeler Transform

    6.5 Associative Coder of Buyanovsky (ACB)

    6.6 Dynamic Markov Compression

    6.7 Summary

    6.8 Projects and Problems


    Lossless Image Compression

    7.1 Overview

    7.2 Introduction

    7.3 CALIC

    7.4 JPEG-LS

    7.5 Prediction Using Conditional Averages

    7.6 Multiresolution Approaches

    7.7 Facsimile Encoding

    7.8 MRC–T.44

    7.9 Summary

    7.10 Projects and Problems


    Mathematical Preliminaries for Lossy Coding

    8.1 Overview

    8.2 Introduction

    8.3 Distortion Criteria

    8.4 Information Theory Revisited

    8.5 Rate Distortion Theory

    8.6 Models

    8.7 Summary

    8.8 Projects and Problems


    Scalar Quantization

    9.1 Overview

    9.2 Introduction

    9.3 The Quantization Problem

    9.4 Uniform Quantizer

    9.5 Adaptive Quantization

    9.6 Nonuniform Quantization

    9.7 Entropy-Coded Quantization

    9.8 Summary

    9.9 Projects and Problems


    Vector Quantization

    10.1 Overview

    10.2 Introduction

    10.3 Advantages of Vector Quantization over Scalar Quantization

    10.4 The Linde-Buzo-Gray Algorithm

    10.5 Tree-Structured Vector Quantizers

    10.6 Structured Vector Quantizers

    10.7 Variations on the Theme

    10.8 Trellis-Coded Quantization

    10.9 Summary

    Further Reading

    10.10 Projects and Problems


    Differential Encoding

    11.1 Overview

    11.2 Introduction

    11.3 The Basic Algorithm

    11.4 Prediction in DPCM

    11.5 Adaptive DPCM

    11.6 Delta Modulation

    11.7 Speech Coding

    11.8 Image Coding

    11.9 Summary

    11.10 Projects and Problems


    Mathematical Preliminaries for Transforms, Subbands, and Wavelets

    12.1 Overview

    12.2 Introduction

    12.3 Vector Spaces

    12.4 Fourier Series

    12.5 Fourier Transform

    12.6 Linear Systems

    12.7 Sampling

    12.8 Discrete Fourier Transform

    12.9 Z-Transform

    12.10 Summary

    12.11 Projects and Problems


    Transform Coding

    13.1 Overview

    13.2 Introduction

    13.3 The Transform

    13.4 Transforms of Interest

    13.5 Quantization and Coding of Transform Coefficients

    13.6 Application to Image Compression– JPEG

    13.7 Application to Audio Compression–The MDCT

    13.8 Summary

    13.9 Projects and Problems


    Subband Coding

    14.1 Overview

    14.2 Introduction

    14.3 Filters

    14.4 The Basic Subband Coding Algorithm

    14.5 Design of Filter Banks

    14.6 Perfect Reconstruction Using Two-Channel Filter Banks

    14.7 M-Band QMF Filter Banks

    14.8 The Polyphase Decomposition

    14.9 Bit Allocation

    14.10 Application to Speech Coding—G.722

    14.11 Application to Audio Coding—MPEG Audio

    14.12 Application to Image Compression

    14.13 Summary

    14.14 Projects and Problems



    15.1 Overview

    15.2 Introduction

    15.3 Wavelets

    15.4 Multiresolution Analysis and the Scaling Function

    15.5 Implementation Using Filters

    15.6 Biorthogonal Wavelets

    15.7 Lifting

    15.8 Summary

    Further Reading

    15.9 Projects and Problems


    Wavelet-Based Image Compression

    16.1 Overview

    16.2 Introduction

    16.3 Embedded Zerotree Coder

    16.4 Set Partitioning in Hierarchical Trees

    16.5 JPEG 2000

    16.6 Summary

    16.7 Projects and Problems


    Audio Coding

    17.1 Overview

    17.2 Introduction

    17.3 MPEG Audio Coding

    17.4 MPEG Advanced Audio Coding

    17.5 Dolby AC-3 (Dolby Digital)

    17.6 Other Standards

    17.7 Summary


    Analysis/Synthesis and Analysis by Synthesis Schemes

    18.1 Overview

    18.2 Introduction

    18.3 Speech Compression

    18.4 Wideband Speech Compression—ITU-T G.722.2

    18.5 Coding of Speech for Internet Applications

    18.6 Image Compression

    18.7 Summary

    18.8 Projects and Problems


    Video Compression

    19.1 Overview

    19.2 Introduction

    19.3 Motion Compensation

    19.4 Video Signal Representation

    19.5 ITU-T Recommendation H.261

    19.6 Model-Based Coding

    19.7 Asymmetric Applications

    19.8 The MPEG-1 Video Standard

    19.9 The MPEG-2 Video Standard—H.262

    19.10 ITU-T Recommendation H.263

    19.11 ITU-T Recommendation H.264, MPEG-4 Part 10, Advanced Video Coding

    19.12 MPEG-4 Part 2

    19.13 Packet Video

    19.14 Summary

    19.15 Projects and Problems


    Appendix A. Probability and Random Processes

    A.1 Probability

    A.2 Random Variables

    A.3 Distribution Functions

    A.4 Expectation

    A.5 Types of Distribution

    A.6 Stochastic Process

    A.7 Projects and Problems


    Appendix B. A Brief Review of Matrix Concepts

    B.1 A Matrix

    B.2 Matrix Operations


    Appendix C. The Root Lattices




Product details

  • No. of pages: 768
  • Language: English
  • Copyright: © Morgan Kaufmann 2012
  • Published: October 4, 2012
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9780124160002

About the Author

Khalid Sayood

Khalid Sayood

Khalid Sayood received his BS and MS in Electrical Engineering from the University of Rochester in 1977 and 1979, respectively, and his Ph.D. in Electrical Engineering from Texas A&M University in 1982. In 1982, he joined the University of Nebraska, where he is the Heins Professor of Engineering. His research interests include data compression, joint source channel coding, and bioinformatics.

Affiliations and Expertise

Department of Electrical and Computer Engineering, University of Nebraska, Lincoln, Nebraska, USA

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