Side information hybrid generation based on improved motion vector field
Side information hybrid generation based on improved motion vector field
复制标题
基于改进运动矢量场的辅助信息混合生成
DOI：
10.1007/s11042-021-10870-8
复制
发表时间：
2021-05-08
影响因子：
3.6
通讯作者：
Chen, Jianhua
中科院分区：
文献类型：
--
作者：
Wang, Wei;Li, Jingjian;Chen, Jianhua
边信息的质量对分布式视频编码系统的性能有着重要的影响。目前，边信息的产生主要是基于平移运动模型，利用帧间相关性进行运动估计。考虑到生成的边信息容易出现块效应和重影，以及未充分考虑非线性运动和未充分利用帧内相关性的情况，提出了一种基于运动矢量场改进模型的边信息混合生成算法。要为当前Wyner-Ziv帧生成的边信息帧被划分为易于估计和难以估计的宏块。对于难以估计的宏块，采用Horn和Schunck稠密光流法生成可靠的运动矢量;对于易于估计的宏块，采用块匹配法生成不可靠的运动矢量，并对不可靠的运动矢量进行修正，然后对修正后的运动矢量进行运动补偿，得到最终的边信息帧。实验结果表明，采用改进的运动矢量场进行运动补偿得到的边信息质量有了明显提高，从而有效地提高了分布式视频编码系统的整体性能。
The quality of side information has an important impact on the performance of a distributed video coding system. At present, the generation of side information is mainly based on the translational motion model using the inter-frame correlation for motion estimation. Considering that the generated side information is prone to block effect and ghosting, as well as the situation that the nonlinear motion is not fully considered and the intra-frame correlation is not fully utilized, a side information hybrid generation algorithm based on an improvement model for the motion vector field is proposed. The side information frame to be generated for the current Wyner-Ziv frame is divided into easy-to-estimate and difficult-to-estimate macroblocks. For difficult-to-estimate macroblocks, the Horn and Schunck dense optical flow method is used to generate reliable motion vectors, for easy-to-estimate macroblocks, the block matching method is used to generate unreliable motion vectors which are modified by the proposed scheme, and then, the improved motion vectors are used for motion compensation to produce the final side information frame. Experiment results show that the quality of side information obtained by using the improved motion vector field for motion compensation has been significantly improved, thus the overall performance of the distributed video coding system has been effectively improved.