In this paper, auto regressive (AR) model is applied to error concealment for block-based packet video coding. In the proposed error concealment scheme, the motion vector for each corrupted block is first derived by any kind of recovery algorithms. Then each pixel within the corrupted block is replenished as the weighted summation of pixels within a square centered at the pixel indicated by the derived motion vector in a regression manner. Two block-dependent AR coefficient derivation algorithms under spatial and temporal continuity constraints are proposed respectively. The first one derives the AR coefficients via minimizing the summation of the weighted square errors within all the available neighboring blocks under the spatial continuity constraint. The confidence weight of each pixel sample within the available neighboring blocks is inversely proportional to the distance between the sample and the corrupted block. The second one derives the AR coefficients by minimizing the summation of the weighted square errors within an extended block in the previous frame along the motion trajectory under the temporal continuity constraint. The confidence weight of each extended sample is inversely proportional to the distance toward the corresponding motion aligned block whereas the confidence weight of each sample within the motion aligned block is set to be one. The regression results generated by the two algorithms are then merged to form the ultimate restorations. Various experimental results demonstrate that the proposed error concealment strategy is able to improve both the objective and subjective quality of the replenished blocks compared to other methods.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here