Analysis of Motion-complexity and Robustness for Video Transmission

In this work, we study the problem of end-to-end video transmission over a noisy communication link, and analytically characterize the complexity (of motion search) and robustness metrics for this problem. The presence of channel noise results in an uncertainty at the encoder as to the information available at the decoder, naturally invoking the framework of source coding with side information (distributed source coding) used in our analysis. We address three important aspects. First, we quantify the theoretical performance gains attained with side-information based codecs over prediction-based coders like MPEG under a lossy transmission scenario when there is drift. Secondly, we show that by accurate DFD (displaced frame difference) modeling we can closely approach MPEG´s compression performance using side-information video coding principles without resorting to long block-length channel codes. Thirdly, we quantify analytically that the value of accurately estimating DFD statistics diminishes, as the channel gets noisier