Second-Generation Error Concealment for Video Transport over Error Prone Channels

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

Iterative joint source channel decoding for H.264 compressed video transmission

In this thesis, the error resilient transmission of H.264 compressed video using Context-based Adaptive Binary Arithmetic Code (CABAC) as the entropy code is examined. The H.264 compressed video is convolutionally encoded and transmitted over an Additive White Gaussian Noise (AWGN) channel. Two iterative joint source-channel decoding schemes are proposed, in which slice candidates that failed semantic verification are exploited. The first proposed scheme uses soft values of bits produced by a soft-input soft-output channel decoder to generate a list of slice candidates for each slice in the compressed video sequence. These slice candidates are semantically verified to choose the best one. A new semantic checking method is proposed, which uses information from slice candidates that failed semantic verification to virtually check the current slice candidate. The second proposed scheme is built on the first one. This scheme also uses slice candidates that failed semantic verification but it uses them to modify soft values of bits at the source decoder before they are fed back into the channel decoder for the next iteration. Simulation results show that both schemes offer improvements in terms of subjective quality and in terms of objective quality using PSNR and BER as measures. Keywords: Video transmission, H.264, semantics, slice candidate, joint source-channel decoding, error resilienc