Low-complexity Distributed Source Coding PDF Download

Author: Haishan Wang
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 152

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Book Description

Author: Shuang Wang
Publisher: John Wiley & Sons
ISBN: 1118705971
Category : Science
Languages : en
Pages : 384

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Book Description
Distributed source coding is one of the key enablers for efficient cooperative communication. The potential applications range from wireless sensor networks, ad-hoc networks, and surveillance networks, to robust low-complexity video coding, stereo/Multiview video coding, HDTV, hyper-spectral and multispectral imaging, and biometrics. The book is divided into three sections: theory, algorithms, and applications. Part one covers the background of information theory with an emphasis on DSC; part two discusses designs of algorithmic solutions for DSC problems, covering the three most important DSC problems: Slepian-Wolf, Wyner-Ziv, and MT source coding; and part three is dedicated to a variety of potential DSC applications. Key features: Clear explanation of distributed source coding theory and algorithms including both lossless and lossy designs. Rich applications of distributed source coding, which covers multimedia communication and data security applications. Self-contained content for beginners from basic information theory to practical code implementation. The book provides fundamental knowledge for engineers and computer scientists to access the topic of distributed source coding. It is also suitable for senior undergraduate and first year graduate students in electrical engineering; computer engineering; signal processing; image/video processing; and information theory and communications.

Author: Pier Luigi Dragotti
Publisher: Academic Press
ISBN: 0080922740
Category : Technology & Engineering
Languages : en
Pages : 359

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Book Description
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. 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

Author: David Prakash Varodayan
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Distributed source coding, the separate encoding and joint decoding of statistically dependent sources, has many potential applications ranging from lower complexity capsule endoscopy to higher throughput satellite imaging. This dissertation improves distributed source coding algorithms and the analysis of their coding performance to handle uncertainty in the statistical dependence among sources. We construct sequences of rate-adaptive low-density parity-check (LDPC) codes that enable encoders to switch flexibly among coding rates in order to adapt to arbitrary degrees of statistical dependence. These code sequences operate close to the Slepian-Wolf bound at all rates. Rate-adaptive LDPC codes with well-designed source degree distributions outperform commonly used rate-adaptive turbo codes. We then consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive performance bounds for binary and multilevel models of this problem and devise coding algorithms for both cases. Each encoder sends some portion of its source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source and the hidden statistical dependence variables. This system performs close to the derived bounds when an appropriate doping rate is selected. We concurrently develop techniques based on density evolution to analyze our coding algorithms. Experiments show that our models closely approximate empirical coding performance. This property allows us to efficiently optimize parameters of the algorithms, such as source degree distributions and doping rates. We finally demonstrate the application of these adaptive distributed source coding techniques to reduced-reference video quality monitoring, multiview coding and low-complexity video encoding.

Author: Shuang Wang
Publisher: John Wiley & Sons
ISBN: 111870598X
Category : Science
Languages : en
Pages : 384

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Book Description
Distributed source coding is one of the key enablers for efficient cooperative communication. The potential applications range from wireless sensor networks, ad-hoc networks, and surveillance networks, to robust low-complexity video coding, stereo/Multiview video coding, HDTV, hyper-spectral and multispectral imaging, and biometrics. The book is divided into three sections: theory, algorithms, and applications. Part one covers the background of information theory with an emphasis on DSC; part two discusses designs of algorithmic solutions for DSC problems, covering the three most important DSC problems: Slepian-Wolf, Wyner-Ziv, and MT source coding; and part three is dedicated to a variety of potential DSC applications. Key features: Clear explanation of distributed source coding theory and algorithms including both lossless and lossy designs. Rich applications of distributed source coding, which covers multimedia communication and data security applications. Self-contained content for beginners from basic information theory to practical code implementation. The book provides fundamental knowledge for engineers and computer scientists to access the topic of distributed source coding. It is also suitable for senior undergraduate and first year graduate students in electrical engineering; computer engineering; signal processing; image/video processing; and information theory and communications.

Author: Huihui Bai
Publisher: Springer Science & Business Media
ISBN: 1447122488
Category : Computers
Languages : en
Pages : 183

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Book Description
This book examines distributed video coding (DVC) and multiple description coding (MDC), two novel techniques designed to address the problems of conventional image and video compression coding. Covering all fundamental concepts and core technologies, the chapters can also be read as independent and self-sufficient, describing each methodology in sufficient detail to enable readers to repeat the corresponding experiments easily. Topics and features: provides a broad overview of DVC and MDC, from the basic principles to the latest research; covers sub-sampling based MDC, quantization based MDC, transform based MDC, and FEC based MDC; discusses Sleplian-Wolf coding based on Turbo and LDPC respectively, and comparing relative performance; includes original algorithms of MDC and DVC; presents the basic frameworks and experimental results, to help readers improve the efficiency of MDC and DVC; introduces the classical DVC system for mobile communications, providing the developmental environment in detail.

Author: Ozgun Bursalioglu
Publisher:
ISBN:
Category : Coding theory
Languages : en
Pages : 112

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Book Description

Author: Maxim Goukhshtein
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
In this work we propose a new method for compressing multiple correlated sources with a very low-complexity encoder in the presence of side information. Our approach uses ideas from compressed sensing and distributed source coding. At the encoder, syndromes of the quantized compressively sensed sources are generated and transmitted. The decoder uses side information to predict the compressed sources. The predictions are then used to recover the quantized measurements via a two-stage decoding process consisting of bitplane prediction and syndrome decoding. Finally, guided by the structure of the sources and the side information, the sources are reconstructed from the recovered measurements. As a motivating example, we consider the compression of multispectral images acquired on board satellites, where resources, such as computational power and memory, are scarce. Our experimental results exhibit a significant improvement in the rate-distortion trade-off when compared against approaches with similar encoder complexity.

Author: Xin Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 300

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Book Description

Author: L Padma Suresh
Publisher: Springer
ISBN: 8132221354
Category : Technology & Engineering
Languages : en
Pages : 846

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Book Description
The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.