Introduction to Data Compression
- 6th Edition - January 1, 2028
- Latest edition
- Author: Khalid Sayood
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 7 3 9 2 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 7 3 9 3 - 3
Introduction to Data Compression, Sixth Edition, builds on the success of what is widely considered the best introduction and reference text on the art and science of data… Read more
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Introduction to Data Compression, Sixth 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.
• Explains established and emerging standards in- depth, including JPEG 2000, JPEG-LS, MPEG-2, H.264, JBIG 2, ADPCM, LPC, CELP, MELP, iLBC and the new HEVC standard
• Includes more coverage of lattices in vector quantization
• Source code is provided via a companion website that gives readers the opportunity to build their own algorithms and choose and implement techniques in their own applications
• Includes more coverage of lattices in vector quantization
• Source code is provided via a companion website that gives readers the opportunity to build their own algorithms and choose and implement techniques in their own applications
Graduate students in data compression, multimedia, and info theory courses at CS/ECE programs
1. Introduction
2. Mathematical Preliminaries for Lossless Compression
3. Huffman Coding
4. Universal Coding
5. Arithmetic Coding
6. Dictionary Techniques
7. Context-Based Compression
8. Lossless Image Compression
9. Mathematical Preliminaries for Lossy Coding
10. Scalar Quantization
11. Vector Quantization
12. Differential Encoding
13. Mathematical Preliminaries for Transforms, Subbands, and Wavelets
14. Transform Coding
15. Subband Coding
16. Wavelets
17. Wavelet-Based Image Compression
18. Audio Coding
19. Analysis/Synthesis and Analysis by Synthesis Schemes
20. Video Compression
APPENDIX A: Probability and Random Processes
APPENDIX B: A Brief Review of Matrix Concepts
APPENDIX C: The Root Lattices
APPENDIX D: Neural Nets
2. Mathematical Preliminaries for Lossless Compression
3. Huffman Coding
4. Universal Coding
5. Arithmetic Coding
6. Dictionary Techniques
7. Context-Based Compression
8. Lossless Image Compression
9. Mathematical Preliminaries for Lossy Coding
10. Scalar Quantization
11. Vector Quantization
12. Differential Encoding
13. Mathematical Preliminaries for Transforms, Subbands, and Wavelets
14. Transform Coding
15. Subband Coding
16. Wavelets
17. Wavelet-Based Image Compression
18. Audio Coding
19. Analysis/Synthesis and Analysis by Synthesis Schemes
20. Video Compression
APPENDIX A: Probability and Random Processes
APPENDIX B: A Brief Review of Matrix Concepts
APPENDIX C: The Root Lattices
APPENDIX D: Neural Nets
- Edition: 6
- Latest edition
- Published: January 1, 2028
- Language: English
KS
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