Second-generation error concealment for video transport over error prone channels

Abstract

Video transport over error prone channels may result in loss or erroneous decoding of the video. Error concealment is an effective mechanism to reconstruct the video content. In this paper, we review different error concealment methods and introduce a new framework, which we refer to as second-generation error concealment. All the error concealment methods reconstruct the lost video content by making use of some a priori knowledge about the video content. First-generation error concealment builds such a priori in a heuristic manner. The proposed second-generation error concealment builds the a priori by modeling the statistics of the video content. Context-based models are trained with the correctly decoded video content, and then used to replenish the lost video content. Trained models capture the statistics of the video content and thus reconstruct the lost video content better than reconstruction by heuristics.