Auto Regressive Model and Weighted Least Squares Based Packet Video Error Concealment

In this paper, auto regressive (AR) model is applied to error concealment for block-based packet video encoding. Each pixel within the corrupted block is restored as the weighted summation of corresponding pixels within the previous frame in a linear regression manner. Two novel algorithms using weighted least squares method are proposed to derive the AR coefficients. First, we present a coefficient derivation algorithm under the spatial continuity constraint, in which the summation of the weighted square errors within the available neighboring blocks is minimized. The confident weight of each sample is inversely proportional to the distance between the sample and the corrupted block. Second, we provide a coefficient derivation algorithm under the temporal continuity constraint, where the summation of the weighted square errors around the target pixel within the previous frame is minimized. The confident weight of each sample is proportional to the similarity of geometric proximity as...

• Type: Conference
• Year: 2010
• Where: DCC
• Authors: Yongbing Zhang, Xinguang Xiang, Siwei Ma, Debin Zhao, Wen Gao
• Keywords: Coefficient Derivation Algorithm, Computer Graphics, DCC 2010, Error Concealment, Weighted Square Errors