William A. Pearlman

Digital Signal Compression (eBook, PDF)

Principles and Practice

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 27. Oktober 2011
• Englisch
• ISBN-13: 9781139118675
• Artikelnr.: 38277432

Autorenporträt

William A. Pearlman is a Professor in the Electrical, Computer and Systems Engineering Department at the Rensselaer Polytechnic Institute (RPI), where he has been a faculty member since 1979. He has more than 35 years of experience in teaching and researching in the fields of information theory, data compression, digital signal processing and digital communications theory. He is a Fellow of the IEEE and the SPIE, and is the co-inventor of two celebrated image compression algorithms: SPIHT and SPECK.

Inhaltsangabe

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.