Abstract: In order to remove the image blurring caused by reconstructing video frames independently frame by frame using traditional compressed video sensing method, this paper proposed a new approach to video compressed sensing based on motion estimation and motion compensation by combining the compressed sensing theory with related technology of MPEG standard video coding, so as to remove the spatial and temporal redundancy of video signal. This method took full account of the temporal correlations of video sequences and firstly compensated video frames using forward, backward and bidirectional prediction, then adopted the Backtracking-based Adaptive Orthogonal Matching Pursuit (BAOMP) algorithm to reconstruct the motion prediction residuals and finally reconstructed current frames. The experimental results indicate that the proposed method can gain a better video image quality compared with frame-by-frame reconstruction method and achieve a higher Peak Signal-to-Noise Ratio (PSNR).

Key words: compressed sensing, video compression, motion estimation, temporal correlation, Backtracking-based Adaptive Orthogonal Matching Pursuit (BAOMP)

摘要： 为了解决传统视频压缩传感方法中对视频逐帧单独重构所产生的图像模糊,将压缩传感理论与MPEG标准视频编码的相关技术相结合,提出了一种基于运动估计与运动补偿的视频压缩传感方法,以消除视频信号在空域和时域上的冗余。该方法在充分考虑视频序列时域相关性的同时,首先对视频图像进行前、后向和双向预测和补偿,然后采用回溯自适应正交匹配追踪(BAOMP)算法,对运动预测残差进行重构,最后实现当前帧的重构。实验结果表明,该方法较逐帧重构的视频图像质量有较大改善,且可获得更高的峰值信噪比。

关键词: 压缩传感, 视频压缩, 运动估计, 时域相关性, 回溯自适应正交匹配追踪