基于边信息的分布式视频压缩感知的残差重构

摘要

Compressed sensing(CS)combines video signal transformation and compression,a new method for simplifying the coding algorithms is proposed.A simple video coding by integrating the DVC and CS is built in this paper,and it proposes a new residual recovery of compressive video sensing based on side information using the correlations of source video and side information.At the encoder,it just encodes each key frame by traditional intra-frame and measured the other non-key frames randomly.At the decoder,it implementes the efficient reconstruction using modified side information and measurements.The experiment results show that the proposed method achieves 4 ～6 dB improvements in PSNR compared to the referenced scheme in the smoothed video.%压缩感知(Compressed Sensing,CS)结合了视频信号的变换和信息压缩过程,为简化编码算法提供了一种新的解决思路.把分布式视频编码(DVC)和CS结合在一起,构建简单的视频编码框架,并利用原始视频帧与边信息之间的相关性进行残差重构,提出了一种基于边信息的分布式视频压缩感知编解码方案.此方法对关键帧采用传统的帧内编、解码；对非关键帧CS进行随机观测提取观测向量,解码端利用优化的边信息和传输的CS观测向量进行联合重构.实验结果表明,该方法在运动较平滑的序列中比参考方案的恢复质量提高了4 ～6 dB.