Information Flows in Video Coding

We study information theoretical performance of common video coding methodologies at the frame level. Via an abstraction of consecutive video frames as correlated random variables, many existing video coding techniques, including the baseline of MPEG-x and H.26x, the scalable coding and the distributed video coding, can have corresponding information theoretical models. The theoretical achievable rate distortion regions have been completely solved for some systems while for others remain open. We show that the achievable rate region of sequential coding equals to that of predictive coding for Markov sources. We give a theoretical analysis of the coding efficiency of B frames in the popular hybrid video coding architecture, bringing new understanding of the current practice. We also find that distributed sequential video coding generally incurs a performance loss if the source is not Markov.