In this paper, we investigate the efficacy of the weighted prediction feature provided within H.264/AVC video coding
standard for error resilient video streaming. Leaky prediction has been proposed for scalable and non-scalable video
coding to effectively combat transport errors. However, all prior results are based on non standard coding methods and
no results have been available on the effectiveness of leaky prediction that is supported by a video coding standard. The
weighted prediction feature in H.264/AVC was originally designed for improving the coding efficiency especially in
presence of fading in video sequences. This paper presents a performance analysis of H.264/AVC weighted prediction
feature that balances the trade-off between coding efficiency and error resilience. A theoretical analysis of rate-distortion
performance of leaky prediction is provided and closed-form rate-distortion functions are derived for the error free and
error drift scenarios. The theoretical results conform well to the operational results with respect to different choices of
the leaky factor.
The JPEG2000 coding scheme is slowly getting into use in imaging applications. The standard offers a set of new features and a better compression efficiency compared to the baseline JPEG. It requires, however, a high computational cost, making its usage in constrained devices, such as mobile phones or PDAs, challenging. We present a precompression rate allocation technique to reduce the encoding complexity and help adoption of JPEG2000 in such contexts.
The use of forward error-control (FEC) coding, possibly in conjunction with ARQ techniques, has emerged as a promising approach for video transport over ATM networks for cell-loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery capabilities it also introduces transmission overhead which can possibly cause additional cell losses. A methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of decoded cell loss probability, using interlaced FEC codes. The transport channel is modelled as a block interference channel (BIC) and the multiplexer as single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, the described methodology provides theoretically achievable upper limits on the number of sources multiplexed. Performance of specific coding techniques using interlaced nonbinary Reed-Solomon (RS) codes and binary rate-compatible punctured convolutional (RCPC) codes is illustrated.
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