Refining Side Information for Improved Transform Domain Wyner-Ziv Video Coding
Refining Side Information for Improved Transform Domain Wyner-Ziv Video Coding
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DOI：
10.1109/tcsvt.2009.2022783
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发表时间：
2009-09
影响因子：
8.4
通讯作者：
R. Martins;Catarina Brites;J. Ascenso;F. Pereira
中科院分区：
文献类型：
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作者：
R. Martins;Catarina Brites;J. Ascenso;F. Pereira
wner - ziv （WZ）视频编码是分布式视频编码的一种特殊情况，它是一种基于睡眠狼定理和WZ定理的最新视频编码范式。与现有的基于预测的标准视频编解码器相反，WZ视频编码利用解码器的源统计信息，从而允许开发更简单的编码器。到目前为止，WZ视频编码并没有达到传统视频编码方案的压缩效率性能，主要原因是最流行的WZ视频编解码器中，边信息的质量较差，边信息是对解码器处创建的原始帧的估计。在此背景下，本文提出了一种新的基于学习方法的变换域WZ视频编解码器侧信息改进（SIR）算法，该算法在解码过程中不断改进侧信息。结果显示，在最先进的WZ和标准视频编解码器方面，特别是在高动态内容和长图片大小等关键条件下，性能得到了显著和一致的改善。
Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, which is a recent video coding paradigm based on the Slepian-Wolf and WZ theorems. Contrary to available prediction-based standard video codecs, WZ video coding exploits the source statistics at the decoder, allowing the development of simpler encoders. Until now, WZ video coding did not reach the compression efficiency performance of conventional video coding solutions, mainly due to the poor quality of the side information, which is an estimate of the original frame created at the decoder in the most popular WZ video codecs. In this context, this paper proposes a novel side information refinement (SIR) algorithm for a transform domain WZ video codec based on a learning approach where the side information is successively improved as the decoding proceeds. The results show significant and consistent performance improvements regarding state-of-the-art WZ and standard video codecs, especially under critical conditions such as high motion content and long group of pictures sizes.