Enhancing error resiliency for multi-hypothesis video coding techniques

In this paper, two techniques based on the optimization of end-to-end distortions in presence of channel errors, are proposed to enhance the error resiliency of the multi-hypothesis coded videos. First, an error resilient motion estimation algorithm is introduced for a given hypothesis-weighting vector to consider the error resiliency, in addition to the traditional coding efficiency. Second, based on the availability of MVs, the proposed adaptive hypothesis-weighting algorithm makes error resiliency adaptive to video contents, frame by frame. Experiment results show that both techniques are capable of improving PSNR performance by up to 1 dB when the packet loss rate is 15%.