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Optimal priority MDC video streaming for networks with path diversity

机译:具有路径分集的网络的最佳优先级MDC视频流

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This paper proposes a robust video streaming scheme for priority networks with path diversity, based on a combined approach of multiple description coding (MDC) with optimal picture classification into two priorities. A binary classification algorithm is proposed to define high (HP) and low (LP) priority network abstraction layer units (NALU), which in turn define the packet priorities. An optimisation algorithm is used to find HP pictures, based on dynamic programming and relying on minimisation of the packet loss concealment distortion. The paper shows that the proposed algorithm is able to effectively improve the decoded video without increasing the MDC stream redundancy. The overall performance evaluation, carried out by simulating MDC video streaming over lossy networks with path diversity, demonstrates that the proposed algorithm yields higher video quality for a wide range of packet loss rates (PLR). Comparing with no-priority MDC video streaming schemes, the simulation results show that the proposed algorithm can improve the average PSNR results in 0.7–3.2dB for packet loss rates between 3% and 15%.
机译:本文提出了一种具有优先权的网络,具有路径分集的鲁棒视频流方案,该方案基于将多图片编码分为两个优先级的多描述编码(MDC)的组合方法。提出了一种二进制分类算法来定义高(HP)和低(LP)优先级的网络抽象层单元(NALU),进而定义数据包的优先级。基于动态编程并依靠最小化丢包掩盖失真的优化算法用于查找HP图片。本文表明,该算法能够在不增加MDC流冗余的情况下,有效地改善解码视频。通过模拟具有路径分集的有损网络上的MDC视频流进行的整体性能评估表明,对于宽范围的丢包率(PLR),该算法可产生更高的视频质量。与无优先级的MDC视频流传输方案相比,仿真结果表明,对于3%至15%的丢包率,该算法可以将平均PSNR结果提高0.7-3.2dB。

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