Introduction to Data Compression, Fifth Edition, builds on the success of what is widely considered the best introduction and reference text on the art and science of data compression.
Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio and video. This new edition includes all the latest developments in the field.
Khalid Sayood 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, the book includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, and scalar and vector quantization.
The book provides a comprehensive working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Für höhere Schule und Studium
Graduate students in data compression, multimedia, and info theory courses at CS/ECE programs; software and hardware engineers; networking and database professionals working with data and file compression
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 236 mm
Breite: 189 mm
Dicke: 43 mm
Gewicht
ISBN-13
978-0-12-809474-7 (9780128094747)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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.
Autor*in
Department of Electrical and Computer Engineering, University of Nebraska, Lincoln, Nebraska, USA
1. Introduction
2. Mathematical Preliminaries for Lossless Compression
3. Huffman Coding
4. Arithmetic Coding
5. Dictionary Techniques
6. Context-Based Compression
7. Lossless Image Compression
8. Mathematical Preliminaries for Lossy Coding
9. Scalar Quantization
10. Vector Quantization
11. Differential Encoding
12. Mathematical Preliminaries for Transforms, Subbands, and Wavelets
13. Transform Coding
14. Subband Coding
15. Wavelets
16. Wavelet-Based Image Compression
17. Audio Coding
18. Analysis/Synthesis and Analysis by Synthesis Schemes
19. Video Compression
APPENDIX A: Probability and Random Processes
APPENDIX B: A Brief Review of Matrix Concepts
APPENDIX C: The Root Lattices
