Embedded Multiple Description Coding of Video

Abstract

Abstract-Real-time delivery of video over best-effort errorprone packet networks requires scalable erasure-resilient compression systems in order to 1) meet the users' requirements in terms of quality, resolution, and frame-rate; 2) dynamically adapt the rate to the available channel capacity; and 3) provide robustness to data losses, as retransmission is often impractical. Furthermore, the employed erasure-resilience mechanisms should be scalable in order to adapt the degree of resiliency against transmission errors to the varying channel conditions. Driven by these constraints, we propose in this paper a novel design for scalable erasure-resilient video coding that couples the compression efficiency of the open-loop architecture with the robustness provided by multiple description coding. In our approach, scalability and packet-erasure resilience are jointly provided via embedded multiple description scalar quantization. Furthermore, a novel channel-aware rate-allocation technique is proposed that allows for shaping on-the-fly the output bit rate and the degree of resiliency without resorting to channel coding. As a result, robustness to data losses is traded for better visual quality when transmission occurs over reliable channels, while erasure resilience is introduced when noisy links are involved. Numerical results clearly demonstrate the advantages of the proposed approach over equivalent codec instantiations employing 1) no erasure-resilience mechanisms, 2) erasure-resilience with nonscalable redundancy, or 3) data-partitioning principles.Index Terms-Multiple description coding, packet erasure resilience, scalable video coding.

Tree-Structured Multiple Description Coding for Multiview Mobile TV and Camera-Phone Networks

“…1 [18], [19] provides the lower bound of the achievable MDC performance and may always be employed for practical video streaming applications to transmit the same bitstream via different channels and routes in order to combat the packet loss events imposed by network congestion. In this section, we compare our system's performance to simulcast-SDC.…”

Scalable Joint Source and Channel Coding of Meshes

“…In the L-2 case, used in (10) represents the decrease in distortion in between two successive truncation points, which can be estimated similar to the solution adopted within JPEG-2000 [27], [28]. In the L-infinite case, the eligible truncation points are only the end of the bitplanes [24], [25].…”

“…In the case of an L-2 distortion metric, expression (2) for is well-known, and the factors depend on the gains of the wavelet filters; we gave an example of this expression for video in [27].…”

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