Distributed Video Compressive Sensing Reconstruction Used Nonlocal Similarity

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), The sparse priors has only been exploited to not preserve the edges and textures of video frames well, the nonlocal similarity regularization term has been introduced to joint reconstruction model in order to effectively remove the blurs and blocking artifacts in the edge and texture regions. The simulation experiments show that the proposed joint reconstruction algorithm can effectively improve the objective and subjective quality of video, and enhance the rate-distortion performance of DVCS system at the cost of a certain computational complexity.