基于迭代收缩法和三维复数小波的视频压缩传感重构

分析了压缩传感逐帧重构视频信号的不足.针对这种方法的缺点,提出了一种多帧按组重构的压缩传感视频重构算法.在观测阶段对视频帧逐帧进行随机观测,在重构阶段利用视频信号帧内、帧间的相关性,将多帧视频信号看作三维信号,采用迭代收缩法在每步的迭代过程中用残差来更新重构信号,并利用三维变换,如三维双树复数小波变换等对每步选代后的重构信号进行阈值处理.实验结果表明,能通过随机观测值精确的重构原始视频,达到较高的信噪比,说明有效地利用了视频帧问的相关性,消除了逐帧重构时的帧间抖动现像.

Compressed Sensing Video Reconstruction Based on Iterative Shrinkage and 3D Complex Wavelet

Since the compressed sensing video reconstruction frame by frame suffers interframe dithering, a multi-frame reconstruction algorithm of compressed sensing by group is presented. First, observe randomly frame by frame, and then make use of interframe correlation as three-dimensional signal. Second, in each step of the iterative process, update the reconstructed video by using the residuals. Finally, carry out the signal threshold processing based on three-dimensional transform, such as the 3D Dual-Tree Complex Wavelet Transform etc. Experimental results show that it can precisely reconstruct the original video by using randomly observed values, and achieve a higher signal to noise ratio. It is shown that algorithm uses the relevance of video frames effectively to eliminate the interframe dithering in reconstruction frame by frame.