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Digital Signal Compression

Digital Signal Compression
Principles and Practice

$75.00 ( ) USD

  • Date Published: March 2012
  • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • format: Adobe eBook Reader
  • isbn: 9781139118675

$ 75.00 USD ( )
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About the Authors
  • 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.

    • 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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    Product details

    • 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.

  • Resources for

    Digital Signal Compression

    William A. Pearlman, Amir Said

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    These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.

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  • Instructors have used or reviewed this title for the following courses

    • Cryptography and data compression
    • Principles of Digital Communications
    • Signal Compression
    • Topics in Signal Processing: Data Compression
  • Authors

    William A. Pearlman, Rensselaer Polytechnic Institute, New York
    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, Hewlett-Packard Laboratories, Palo Alto, California
    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 Society.

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