利用指数幂模型进行视频编码

Thomas Maugey, Jérôme Gauthier, B. Pesquet-Popescu, C. Guillemot
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引用次数: 10

摘要

在Wyner-Ziv编码方案中,拉普拉斯模型是涡轮解码器相关噪声估计的标准分布。在实践中,这个假设并不总是被满足,而且估计的模型通常与误差分布明显不同。在这项工作中,我们证明了使用更适合真实分布的模型可以提高性能,因此我们建议使用从未在分布式视频编码环境中测试过的更一般的指数功率分布(EPD)。在几个视频序列上的结果表明,EPD模型在率失真方面优于拉普拉斯模型,在离线(oracle)和在线(实际实现)模式下都优于拉普拉斯模型。这些结果还表明,在某些情况下,在线EPD模型甚至比离线拉普拉斯模型更能降低比特率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using an exponential power model forwyner ziv video coding
The Laplacian model is the standard distribution for correlation noise estimation at the turbodecoder in Wyner-Ziv coding schemes. In practice, this hypothesis is not always satisfied and, regularly, the estimated model sensibly differs from the error distribution. In this work, we prove that using a model better fitted to the true distribution improves the performances, and we thus propose to use the more general exponential power distribution (EPD) which has never been tested in a distributed video coding context. Gains in rate-distortion over the Laplacian model are illustrated by results on several video sequences, showing that the EPD model outperforms the Laplacian one in off-line (oracle) as well as in on-line (practical implementation) modes. These results also indicate that, in some cases, the online EPD model reduces the bitrate even over the off-line Laplacian model.
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