灵活的视频解码:一种分布式源编码方法

Ngai-Man Cheung, Antonio Ortega
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引用次数: 23

摘要

我们研究视频压缩技术来解决需要灵活视频解码的问题。在这些情况下,编码器可以访问许多候选预测器,这些预测器允许它利用源信号相关性,但是在解码器上只有这些预测器的一个子集可用。关键是,编码器不知道哪些预测因子是可用的。灵活的解码在许多应用中都很重要,包括逐帧前向和后向视频播放、多视图视频、比特流交换、鲁棒视频传输等。支持灵活解码的主要挑战是编码器需要在解码器预测器的不确定性下压缩当前帧。一种基于传统“闭环”预测的方法,例如视频中的运动补偿预测(MCP)编码,可以通过在比特流中包含多个可能的预测残差来开发,但是如果支持所有可能的预测器组合,这将导致相当大的编码性能损失,或者如果只有一些组合是漂移。此外,一般不可能保证不同预测情景下的解码版本是相同的。在本文中,我们提出了一种基于分布式源编码(DSC)的算法来解决这个问题。该算法的主要新颖之处在于它在DSC框架内结合了不同的宏块模式和意义编码。这与明智地利用相关统计数据相结合,使我们能够获得具有竞争力的编码性能。以向前/向后视频播放为例,我们证明了该算法优于基于MCP编码的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Video Decoding: A Distributed Source Coding Approach
We investigate video compression techniques to address problems that require flexible video decoding. In these, the encoder has access to a number of candidate predictors that allow it to exploit source signal correlation, but only a subset of these predictors will be available at the decoder. Crucially, the encoder does not know which predictors will be available. Flexible decoding is important in a number of applications including frame-by-frame forward and backward video playback, multiview video, bitstreams switching, robust video transmission, etc. The main challenge to support flexible decoding is that the encoder needs to compress a current frame under the uncertainty on the predictor at decoder. An approach based on conventional "closed loop" prediction, e.g., motion-compensated predictive (MCP) coding in the case of video, could be developed by including multiple possible prediction residues in the bitstream, but this would lead to a considerable coding performance penalty, if all possible predictor combinations are supported, or to drifting, if only some combinations are. Moreover, it is not possible in general to guarantee that decoded versions under different prediction scenarios will be identical. In this paper, we propose a distributed source coding (DSC) based algorithm to tackle the problem. The main novelties of the proposed algorithm are that it incorporates different macroblock modes and significance coding within the DSC framework. This, combined with a judicious exploitation of correlation statistics, allows us to achieve competitive coding performance. Using forward/backward video playback as an example, we demonstrate the proposed algorithm can outperform a solution based on MCP coding.
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