Weighted distortion methods for error resilient video coding
Mr. Geoffrey Sunday Maucho
Date: Friday, April 27, 2012 at 9:30 a.m.
Conference Room 603, McConnell Engineering Building
Wireless and Internet video applications are hampered by bit errors and packet errors, respectively. In addition, packet losses in best effort Internet applications limit video communication applications. Because video compression uses temporal prediction, compressed video is especially susceptible to the problem of transmission errors in one frame propagating into subsequent frames. It is therefore necessary to develop methods to improve the performance of compressed video in the face of channel impairments. Recent work in this area has focused on estimating the end-to-end distortion, which is shown to be useful in building an error resilient encoder. However, these techniques require an accurate estimate of the channel conditions, which is not always accessible for some applications.
Recent video compression standards have adopted a Rate Distortion Optimization (RDO) framework to determine coding options that address the trade-off between rate and distortion. In this dissertation, error robustness is added to the RDO framework as a design consideration. This dissertation studies the behavior of motion-compensated prediction (MCP) in a hybrid video coder, and presents techniques of improving the performance in an error prone environment. An analysis of the motion trajectory gives us insight on how to improve MCP without explicit knowledge of the channel conditions. Information from the motion trajectory analysis is used in a novel way to bias the distortion used in RDO, resulting in an encoded bitstream that is both error resilient and bitrate efficient.
We also present two low complexity solutions that exploit past inter-frame dependencies. In order to avoid error propagation, regions of a frame are classified according to their potential of having propagated errors. By using this method, we are then able to steer the MCP engine towards areas that are considered ``safe" for prediction. Considering the impact error propagation may have in a RDO framework, our work enhances the overall perceived quality of compressed video while maintaining high coding efficiency. Comparison with other error resilient video coding techniques show the advantages offered by the weighted distortion techniques we present in this dissertation.
Mr. Geoffrey Sunday Maucho has pursued his degree with supervisor Professor Fabrice Labeau.
