An improved error concealment by diminishing the edge discontinuity
Jun-Horng Chen · 2011
This work aims to improve the error concealment quality of sparse modeling of which the concealed quality is highly dependent on the structure of the lost image block. It is demonstrated that if the edge discontinuity can be diminished, the concealed quality can be raised. Therefore, this work will define a cost function of edge discontinuity. When the coefficient vector of the sparse model moves towards the direction of the maximum gradient, the cost function of discontinuity will be lowered and the concealed quality can thus be improved. The simulation results will show that the proposed approach indeed improves the performance of error concealment and the improving gain is about 2 ~ 4 dB of PSNR.