Digital Signal Compression

Digital Signal Compression : Principles and Practice

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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 more

Product details

  • Electronic book text | 416 pages
  • Cambridge University Press (Virtual Publishing)
  • Cambridge, United Kingdom
  • English
  • 175 b/w illus. 39 tables 71 exercises
  • 1139118676
  • 9781139118675

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 more

About William A. Pearlman

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. Amir Said is currently a Master Researcher at Hewlett-Packard Laboratories, where he has worked since 1998. His research interests include multimedia communications, coding and information theory, image and video compression, signal processing and optimization, and he has more than 50 publications in these fields. He is co-inventor with Dr Pearlman of the SPIHT image compression algorithm and co-recipient, also with Dr Pearlman, of two Best Paper Awards, one from the IEEE Circuits and Systems Society and the other from the IEEE Signal Processing more