Chapter 1: Invited Addresses and Tutorials on Signals, Coding,
  Systems and Intelligent Techniques

Title: Multiple Description Coding for Scalable Multimedia Coding

Author(s): Peter Schelkens

Address: Vrije Universiteit Brussel (VUB)

Reference: 12th International Workshop on Systems, Signals and Image Processing pp. 47 - 48

Abstract/Summary: Real-time delivery of multimedia contents involves heterogeneous links featuring different reliability and bandwidth provision – e.g. wireless/wired. As a result, data packets sent through best-effort networks may be lost and retransmission is often impractical as it increases congestion and introduces excessive delay. In such scenarios, it is essential to develop image/video coding techniques providing resiliency against network erasures. This problem is efficiently addressed by multiple description coding (MDC). MDC techniques generate two (or more) complementary representations of the input, called descriptions, which are sent to the receiver (typically) over different links. In case of channel impairments, the decoder approximates the original signal by using the available descriptions. Distortion in the reconstructed signal decreases upon reception of any additional description and is lower-bounded by the distortion attained by single description coding (SDC), operating at the same overall bit-rate in an error-free transmission scenario. Techniques such as data partitioning, transform coding (e.g. pairwise correlating transforms and frame expansions), multiple description scalar quantization and forward error correction provide practical instantiations of the MDC concept. Within the broad scope of MDC applications, ranging from still image transmission to multimedia streaming, its application in scalable video coding (SVC) will be illustrated. A recently proposed SVC scheme, coupling the compression efficiency of the open-loop architecture with the robustness of MDC, features a novel framework that selects the amount of resiliency after compression has been performed. This approach adjusts robustness to transmission errors without additional encoding operations. As a result, given the channel statistics, robustness to data losses is traded for better visual quality when transmission occurs over reliable channels, – i.e. MDC approaches the SDC coding performance – while error resilience is introduced when noisy links are involved.

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