Side information hybrid generation based on improved motion vector field

摘要

The quality of side information has an important impact on the performance of a distributed video coding system. At present, the generation of side information is mainly based on the translational motion model using the inter-frame correlation for motion estimation. Considering that the generated side information is prone to block effect and ghosting, as well as the situation that the nonlinear motion is not fully considered and the intra-frame correlation is not fully utilized, a side information hybrid generation algorithm based on an improvement model for the motion vector field is proposed. The side information frame to be generated for the current Wyner-Ziv frame is divided into easy-to-estimate and difficult-to-estimate macroblocks. For difficult-to-estimate macroblocks, the Horn and Schunck dense optical flow method is used to generate reliable motion vectors, for easy-to-estimate macroblocks, the block matching method is used to generate unreliable motion vectors which are modified by the proposed scheme, and then, the improved motion vectors are used for motion compensation to produce the final side information frame. Experiment results show that the quality of side information obtained by using the improved motion vector field for motion compensation has been significantly improved, thus the overall performance of the distributed video coding system has been effectively improved.