Distributed Multiple Description Coding

Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

The explosive growth of network, multimedia and wireless technology is fundamentally changing the way people communicate, fueling demand for reliable real-time transmission of image and video data.
This unique text/reference systematically examines the issues in distributed video coding (DVC) and multiple description coding (MDC), two novel techniques designed to address the problems of conventional image and video compression coding. The book begins with a state-of-the-art survey of the topic, before proposing new methods for improving the performance of image and video transmission using DVC and MDC. 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 researchCovers sub-sampling based MDC, quantization based MDC, transform based MDC, and FEC based MDCDiscusses Sleplian-Wolf coding based on Turbo and LDPC respectively, and comparing relative performanceIncludes original algorithms of MDC and DVCPresents the basic frameworks and experimental results, to help readers improve the efficiency of MDC and DVCIntroduces the classical DVC system for mobile communications, providing the developmental environment in detailResearchers and engineers will find this book a useful reference on DVC and MDC technologies, and a guide for developing practical applications for DVC and MDC systems. The text will also be of interest to graduate students in image processing and signal processing.

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.

Presents a state-of-the-art survey of distributed video coding (DVC) and multiple description coding (MDC)