Correlation estimation with particle-based belief propagation for distributed video coding

In this paper, we propose an adaptive Distributed Video Coding (DVC) scheme that dynamically estimates correlation statistics of the scene in a video sequence to enhance belief-propagation (BP) Slepian-Wolf (SW) decoding. In order to exploit the robustness of distributed source coding (DSC) designs, we integrate particle filtering with standard BP decoding in one factor graph to estimate online correlation among source and side information. Our proposed system boasts improved performance over classical DVC without correlation estimation, due to improved knowledge of correlation statistics via the combination of bit-plane coding and particle-based BP tracking in each frame, as shown by our results.