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Introduction to Data Compression / Edition 4

Introduction to Data Compression / Edition 4

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by Khalid Sayood

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ISBN-10: 0124157963

ISBN-13: 9780124157965

Pub. Date: 10/29/2012

Publisher: Elsevier Science

The need to efficiently store, manipulate, and transmit large masses of information is growing more rapidly than the capacity of systems to handle it. Engineers and computer scientists need a solid understanding of compression in order to work with the burgeoning variety of data types and increasingly data-intensive applications. This uniquely comprehensive book


The need to efficiently store, manipulate, and transmit large masses of information is growing more rapidly than the capacity of systems to handle it. Engineers and computer scientists need a solid understanding of compression in order to work with the burgeoning variety of data types and increasingly data-intensive applications. This uniquely comprehensive book explains the fundamental theories and techniques of data compression, with the most complete coverage available of both lossy and lossless methods. Rather than simply describing current approaches, Sayood explains the theoretical underpinnings of the algorithms so that readers learn how to model structures in data and design compression packages of their own.

Practitioners, researchers, and students will benefit from the balanced presentation of theoretical material and implementations.

  • Covers both lossy and lossless compression techniques with applications to image, speech, text, audio, and video compression.
  • Official compression standards for video, audio, text, and facsimile are discussed in order to illustrate the techniques: includes JPEG, MPEG, G.728, H.261, and Group 3 and 4 fax standards.
  • Detailed examples follow each new concept or algorithm.
  • Software implementations and sample data sets are available, allowing readers to work through the examples in the book and to experiment with various compression techniques on their own.
  • Optional starred sections provide enhanced technical or theoretical discussions.
  • Appendices on probability theory, random processes, and matrix concepts are included for reference.

Product Details

Elsevier Science
Publication date:
Morgan Kaufmann Series in Multimedia Information and Systems Series
Edition description:
New Edition
Product dimensions:
9.40(w) x 7.90(h) x 2.10(d)

Table of Contents

Introduction to Data Compression
by Khalid Sayood
    1 Introduction
      1.1 Compression Techniques
        1.1.1 Lossless Compression
        1.1.2 Lossy Compression
        1.1.3 Measures of Performance
      1.2 Modeling and Coding
      1.3 Organization of This Book
      1.4 Summary
      1.5 Projects and Problems

    2 Mathematical Preliminaries
      2.1 Overview
      2.2 A Brief Introduction to Information Theory
      2.3 Models
        2.3.1 Physical Models
        2.3.2 Probability Models
        2.3.3. Markov Models
        2.3.4 Summary
      2.5 Projects and Problems

    3 Huffman Coding
      3.1 Overview
      3.2 "Good" Codes
      3.3. The Huffman Coding Algorithm
        3.3.1 Minimum Variance Huffman Codes
        3.3.2 Length of Huffman Codes
        3.3.3 Extended Huffman Codes
      3.4 Nonbinary Huffman Codes
      3.5 Adaptive Huffman Coding
        3.5.1 Update Procedure
        3.5.2 Encoding Procedure
        3.5.3 Decoding Procedure
      3.6 Applications of Huffman Coding
        3.6.1 Lossless Image Compression
        3.6.2 Text Compression
        3.6.3 Audio Compression
      3.7 Summary
      3.8 Projects and Problems

    4 Arithmetic Coding
      4.1 Overview
      4.2 Introduction
      4.3 Coding a Sequence
        4.3.1 Generating a Tag
        4.3.2 Deciphering the Tag
      4.4 Generating a Binary Code
        4.4.1 Uniqueness and Efficiency of the Arithmetic Code
        4.4.2 Algorithm Implementation
        4.4.3 Integer Implementation
      4.5 Comparison of Huffman and Arithmetic Coding
      4.6 Applications
        4.6.1 Bi-Level Image Compression-The JBIG Standard
        4.6.2 Image Compression
      4.7 Summary
      4.8 Projects and Problems

    5 Dictionary Techniques
      5.1 Overview
      5.2 Introduction
      5.3 Static Dictionary
        5.3.1 Diagram Coding
      5.4 Adaptive Dictionary
        5.4.1 The LZ77 Approach
        5.4.2 The LZ78 Approach
      5.5 Applications
        5.5.1 File Compression-UNIX COMPRESS
        5.5.2 Image Compression-the Graphics Interchange Format (GIF)
        5.5.3 Compression over Modems-V.42 bis
      5.6 Summary
      5.7 Projects and Problems

    6 Lossless Image Compression
      6.1 Overview
      6.2 Introduction
      6.3 Facsimile Encoding
        6.3.1 Run-Length Coding
        6.3.2 CCITT Group 3 and 4-Recommendations T.4 and T.6
        6.3.3 Comparison of MH, MR, MMR, and JBIG
      6.4 Progressive Image Transmission
      6.5 Other Image Compression Approaches
        6.5.1 Linear Prediction Models
        6.5.2 Context Models
        6.5.3 Multiresolution Models
        6.5.4 Modeling Prediction Errors
      6.6 Summary
      6.7 Projects and Problems

    7 Mathematical Preliminaries
      7.1 Overview
      7.2 Introduction
      7.3 Distortion Criteria
        7.3.1 The Human Visual System
        7.3.2 Auditory Perception
      7.4 Information Theory Revisted
        7.4.1 Conditional Entropy
        7.4.2 Average Mutual Information
        7.4.3 Differential Entropy
      7.5 Rate Distortion Theory
      7.6 Models
        7.6.1 Probability Models
        7.6.2 Linear System Models
        7.6.3 Physical Models
      7.7 Summary
      7.8 Projects and Problems

    8 Scalar Quantization
      8.1 Overview
      8.2 Introduction
      8.3 The Quantization Problem
      8.4 Uniform Quantizer
      8.5 Adaptive Quantization
        8.5.1 Forward Adaptive Quantization
        8.5.2 Backward Adaptive Quantization
      8.6 Nonuniform Quantization
        8.6.1 pdf-Optimized Quantization
        8.6.2 Companded Quantization
      8.7 Entropy-Coded Quantization
        8.7.1 Entropy Coding of Lloyd-Max Quantizer Outputs
        8.7.2 Entropy-Constrained Quantization
        8.7.3 High-Rate Optimum Quantization
      8.8 Summary
      8.9 Projects and Problems

    9 Vector Quantization
      9.1 Overview
      9.2 Introduction
      9.3 Advantages of Vector Quantization over Scalar Quantization
      9.4 The Linde-Buzo-Gray Algorithm
        9.4.1 Initializing the LBG Algorithm
        9.4.2 The Empty Cell Problem
        9.4.3 Use of LBG for Image Compression
      9.5 Tree-Structured Vector Quantizers
        9.5.1 Design of Tree-Structured Vector Quantizers
      9.6 Structured Vector Quantizers
        9.6.1 Pyramid Vector Quantization
        9.6.2 Polar and Spherical Vector Quantizers
        9.6.3 Lattice Vector Quantizers
      9.7 Variations on the Theme
        9.7.1 Gain-Shape Vector Quantization
        9.7.2 Mean-Removed Vector Quantization
        9.7.3 Classified Vector Quantization
        9.7.4 Multistage Vector Quantization
        9.7.5 Adaptive Vector Quantization
      9.8 Summary
      9.9 Projects and Problems

    10 Differential Encoding
      10.1 Overview
      10.2 Introduction
      10.3 The Basic Algorithm
      10.4 Prediction in DPCM
      10.5 Adaptive DPCM (ADPCM)
        10.5.1 Adaptive Quantization in DPCM
        10.5.2 Adaptive Prediction in DPCM
      10.6 Delta Modulation
        10.6.1 Constant Factor Adaptive Delta Modulation (CFDM)
        10.6.2 Continuously Variable Slope Delta Modulation
      10.7 Speech Coding
        10.7.1 G.726
      10.8 Summary
      10.9 Projects and Problems

    11 Subband Coding
      11.1 Overview
      11.2 Introduction
      11.3 The Frequency Domain and Filtering
        11.3.1 Filters
      11.4 The Basic Subband Coding Algorithm
        11.4.1 Bit Allocation
      11.5 Application to Speech Coding-G.722
      11.6 Application to Audio Coding-MPEG Audio
      11.7 Application to Image Compression
        11.7.1 Decomposing an Image
        11.7.2 Coding the Subbands
      11.8 Wavelets
        11.8.1 Families of Wavelets
        11.8.2 Wavelets and Image Compression
      11.9 Summary
      11.10 Projects and Problems

    12 Transform Coding
      12.1 Overview
      12.2 Introduction
      12.3 The Transform
      12.4 Transforms of Interest
        12.4.1 Karhunen-Loeve Transform
        12.4.2 Discrete Cosine Transform
        12.4.3 Discrete Sine Transform
        12.4.4 Discrete Walsh-Hadamard Transform
      12.5 Quantization and Coding of Transform Coefficients
      12.6 Application to Image Compression-JPEG
        12.6.1 The Transform
        12.6.2 Quantization
        12.6.3 Coding
      12.7 Application to Audio Compression
      12.8 Summary
      12.9 Projects and Problems

    13 Analysis/Synthesis Schemes
      13.1 Overview
      13.2 Introduction
      13.3 Speech Compression
        13.3.1 The Channel Vocoder
        13.3.2 The Linear Predictive Coder (Gov.Std.LPC-10)
        13.3.3 Code Excited Linear Prediction (CELP)
        13.3.4 Sinusoidal Coders
      13.4 Image Compression
        13.4.1 Fractal Compression
      13.5 Summary
      13.6 Projects and Problems

    14 Video Compression
      14.1 Overview
      14.2 Introduction
      14.3 Motion Compensation
      14.4 Video Signal Representation
      14.5 Algorithms for Videoconferencing and Videophones
        14.5.1 ITU_T Recommendation H.261
        14.5.2 Model-Based Coding
      14.6 Asymmetric Applications
        14.6.1 The MPEG Video Standard
      14.7 Packet Video
        14.7.1 ATM Networks
        14.7.2 Compression Issues in ATM Networks
        14.7.3 Compression Algorithms for Packet Video
      14.8 Summary
      14.9 Projects and Problems

    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

    B A Brief Review of Matrix Concepts
      B.1 A Matrix
      B.2 Matrix Operations

    C Codes for Facsimile Encoding
    D The Root Lattices

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