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The second edition of Introduction to Data Compression builds on the features that made the first the logical choice-for practitioners who need a comprehensive guide to compression for all types of multimedia and instructors who want to equip their students with solid foundations in these increasingly important and diverse techniques.
This book provides an extensive introduction to the theory underlying today's compression techniques, with detailed, instruction for their application. All of the coverage has been updated to reflect the state of the art in data compression, including both new
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Produktbeschreibung
The second edition of Introduction to Data Compression builds on the features that made the first the logical choice-for practitioners who need a comprehensive guide to compression for all types of multimedia and instructors who want to equip their students with solid foundations in these increasingly important and diverse techniques.
This book provides an extensive introduction to the theory underlying today's compression techniques, with detailed, instruction for their application. All of the coverage has been updated to reflect the state of the art in data compression, including both new algorithms and older methods for which new uses are being found. And the downloadable software gives you the opportunity to see firsthand how various algorithms work, to choose and implement appropriate techniques in your own applications, and to build your own algorithms.

Table of contents:
1 Introduction
2 Mathematical Preliminaries for Lossless Compression
3 Huffman Coding
4 Arithmetic Coding
5 Dictionary Techniques
6 Predictive Coding
7 Mathematical Preliminaries for Lossy Coding
8 Scalar Quantization
9 Vector Quantization
10 Differential Encoding
11 Mathematical Preliminaries for Transforms, Subbands, and Wavelets
12 Transform Coding
13 Subband Coding
14 Wavelets
15 Analysis/Synthesis Schemes
16 Video Compression
A Probability and Random Processes
B A Brief Review of Matrix Concepts
Autorenporträt
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 Henson Professor of Engineering. His research interests include data compression, joint source channel coding, and bioinformatics.