中文摘要：

在分布式视频压缩系统中,边信息的质量对编码效率有至关重要的作用。利用已解码图像信息提高边信息质量是近年来研究的热点之一。根据边信息和已解码信息与原始信息之间的噪声关系,该文提出了一种基于多假设运动补偿去噪的迭代边信息改进算法。首先对原始边信息进行多假设运动补偿去噪,生成质量更好而不仅是相似的补偿图像,然后利用每个码平面的解码信息对边信息进行迭代改进。实验结果表明,该算法能减少码流,显著提高Wyner-Ziv（WZ）帧质量,从而有效的改善分布式视频压缩的率失真性能。

英文摘要：

In the Distributed Video Coding（DVC）,the quality of Side Information（SI） has a critical impact on the coding efficiency and Rate-Distortion（RD） performance.Improving SI quality by extracting motion information from decoded frames becomes a new hotspot research area in recent years.According to noise correlation between SI,partial decoded Wyner-Ziv（WZ） frame and source,a novel iterative SI refinement method based on Multi-Hypothesis Motion-Compensated Prediction（MHMCP） denoising is proposed.In this scheme,firstly the original SI is refined by MHMCP denoising and a better motion compensated frame is generated instead of a similar one.Then it is refined iteratively by refinement module after each bit-plane is decoded.Experimental results show that the proposed strategy can significantly improve quality of WZ frames and reduce bit rate,thereby improve effectively the RD performance of DVC.