Error concealment algorithm based on sparse optimization

In this paper, an application of sparse optimization in the error concealment area is proposed. The spatial and temporal formulations of the pixels in the current frame and reference frame are proposed to solve the problem. Based on the sparse characteristics of nature images, we form sparse optimization problems for both formulations. The optimization problem is solved by the primal-dual interior point method. The solutions are combined for better results. By solving for a limited numbers of significant predictors using the sparse optimization, our algorithm performs subjectively and objectively better for the concealed result; compared to two state-of-the-art spatial-temporal hybrid error concealment methods, the proposed methods can improve by up to 0.19 dB and 1.12 dB in PSNR (Peak Signal-to-Noise Ratio).