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).

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.

This book offers a broad overview of distributed video coding (DVC) and multiple description coding (MDC), novel techniques which address problems of conventional image and video compression coding. Coverage ranges from basic principles to the latest research.

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