Distributed Source Coding - 1st Edition - ISBN: 9780123744852, 9780080922744

Distributed Source Coding

1st Edition

Theory, Algorithms and Applications

Authors: Pier Luigi Dragotti Michael Gastpar
eBook ISBN: 9780080922744
Hardcover ISBN: 9780123744852
Imprint: Academic Press
Published Date: 30th January 2009
Page Count: 360
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The advent of wireless sensor technology and ad-hoc networks has made DSC a major field of interest. Edited and written by the leading players in the field, this book presents the latest theory, algorithms and applications, making it the definitive reference on DSC for systems designers and implementers, researchers, and graduate students.

This book gives a clear understanding of the performance limits of distributed source coders for specific classes of sources and presents the design and application of practical algorithms for realistic scenarios. Material covered includes the use of standard channel codes, such as LDPC and Turbo codes, to DSC, and discussion of the suitability of compressed sensing for distributed compression of sparse signals. Extensive applications are presented and include distributed video coding, microphone arrays and securing biometric data.

This book is a great resource covering the breadth and depth of distributed source coding that’s appropriate for everyone from theoreticians to practitioners. – Richard Baraniuk, Rice University

Key Features

Clear explanation of the principles of distributed source coding (DSC), a technology that has applications in sensor networks, ad-hoc networks, and distributed wireless video systems for surveillance Edited and written by the leading players in the field, providing a complete and authoritative reference *Contains all the latest theory, practical algorithms for DSC design and the most recently developed applications


Signal and image processing researchers, R&D engineers, systems designers and implementers and graduate students.

Table of Contents

  1. Foundations of Distributed Source Coding (Krishnan Eswaran and Michael Gastpar, UC Berkeley)
  2. Distributed transform coding (Varit Chaisinthop and Pier Luigi Dragotti, Imperial College London)
  3. Quantization for Distributed Source Coding (David Rebollo-Monedero, Universitat Politecnica de Catalunya, and Bernd Girod, Stanford University)
  4. Zero-error Distributed Source Coding (Ertem Tuncel, Jayanth Nayak, UC at Riverside, Kenneth Rose, UC at Santa Barbara)
  5. Distributed Coding of Sparse Signals (Vivek Goyal, Massachusetts Institute of Technology, Alyson Fletcher, University of California, Berkeley, Sundeep Rangan, Qualcomm Technologies, Inc.)
Algorithms and Applications:
  1. Towards constructive Slepian-Wolf coding schemes (Christine Guillemot and Aline Roumy, INRIA, France)
  2. Distributed Compression in Microphone Array (Olivier Roy, T. Ajdler, R. Konsbruck and Martin Vetterli, Swiss Federal Institute of Technology)
  3. Distributed Video Coding: Basics, Codecs and Performance (Fernando Pereira, Catarina Brites, João Ascenso, IST, Portugal)
  4. Model Based Multi-view Video Compression using Distributed Source Coding Principles (Jayanth Nayak, Bi Song, Ertem Tuncel and Amit Roy Chowdhury, University of California at Riverside)
  5. Distributed Compression of Hyperspectral Imagery (Ngai-Man Cheung and Antonio Ortega, University of South California)
  6. Securing Biometric Data (Anthony Vetro, Mitsubishi Electric Research Labs (MERL), Stark Draper, Univ Wisconsin-Madison, Shantanu Rane, MERL, Jonathan Yedidia, MERL)


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© Academic Press 2009
Academic Press
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About the Author

Pier Luigi Dragotti

Pier Luigi Dragotti is currently a Senior Lecturer in the Electrical and Electronic Engineering Department at Imperial College, London. He has worked as a researcher at Bell Labs and EPFL and is a member of the IEEE Image and MultiDimensional Signal Processing (IMDSP) Technical Committee.

Michael Gastpar

Michael Gastpar is currently an Associate Professor at the University of California, Berkeley. His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. He won the 2002 EPFL Best Thesis Award, an NSF CAREER award in 2004, and an Okawa Foundation Research Grant in 2008.