Digital Signal Compression
Principles and Practice
$72.00 ( ) USD
- William A. Pearlman, Rensselaer Polytechnic Institute, New York
- Amir Said, Hewlett-Packard Laboratories, Palo Alto, California
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With clear and easy-to-understand explanations, this book covers the fundamental concepts and coding methods of signal compression, whilst still retaining technical depth and rigor. It contains a wealth of illustrations, step-by-step descriptions of algorithms, examples and practice problems, which make it an ideal textbook for senior undergraduate and graduate students, as well as a useful self-study tool for researchers and professionals. Principles of lossless compression are covered, as are various entropy coding techniques, including Huffman coding, arithmetic coding and Lempel-Ziv coding. Scalar and vector quantization and trellis coding are thoroughly explained, and a full chapter is devoted to mathematical transformations including the KLT, DCT and wavelet transforms. The workings of transform and subband/wavelet coding systems, including JPEG2000 and SBHP image compression and H.264/AVC video compression, are explained and a unique chapter is provided on set partition coding, shedding new light on SPIHT, SPECK, EZW and related methods.Read more
- Provides clear explanations of the fundamentals, without compromising on rigor
- Includes descriptions of algorithms in set-aside boxes to help the reader understand how to program the algorithm and apply it in practice
- Covers important material not readily available elsewhere, such as dead-zone coding, distributed source coding, image wavelet coding and alphabet partitioning
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- Date Published: March 2012
- format: Adobe eBook Reader
- isbn: 9781139118675
- contains: 175 b/w illus. 39 tables 71 exercises
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
1. Motivation: the importance of compression
2. Book overview
3. Principles of lossless compression
4. Entropy coding techniques
5. Lossy compression of scalar sources
6. Coding of sources with memory
7. Mathematical transformations
8. Rate control in transform coding systems
9. Transform coding systems
10. Set partition coding
11. Subband/wavelet coding systems
12. Methods for lossless compression of images
13. Color and multi-component image and video coding
14. Distributed source coding.
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