An Iterative Side Information Refinement Method Based on MHMCP Denoising in Distributed Video Coding

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.