Error concealment with multiscale patch clustering and low-rank minimization

In this paper, we propose a novel error concealment method based on multiscale patch clustering and low-rank minimization. In order to collect more reliable patches to form a genuine low-rank matrix, an image pyramid is formed utilizing an effective down-sampling process. The classic singular value thresholding (SVT) is modified into a global iteration to solve the low-rank minimization problem. Extensive experimental results on the random pixel loss and the block loss situation validate the effectiveness of the proposed method. The proposed method acquires higher PSNR and better visual quality than the state-of-the-art low-rank based error concealment methods.