Motion vector coding algorithm based on adaptive template matching

Motion estimation as well as the corresponding motion compensation is a core part of modern video coding standards, which highly improves the compression efficiency. On the other hand, motion information takes considerable portion of compressed bit stream, especially in low bit rate situation. In this paper, an efficient motion vector prediction algorithm is proposed to minimize the bits used for coding the motion information. First, a possible motion vector predictor (MVP) candidate set (CS) including several scaled spatial and temporal predictors is defined. To increase the diversity of predictors, the spatial predictor is adaptively changed based on current distribution of neighboring motion vectors. After that, adaptive template matching technique is applied to remove non-effective predictors from the CS so that the bits used for the MVP index can be significantly reduced. As the final MVP is chosen based on minimum motion vector difference criterion, a guessing strategy is further introduced so that in some situations the bits consumed by signaling the MVP index to the decoder can be totally omitted. The experimental results indicate that the proposed method can achieve an average bit rate reduction of 5.9% compared with the H.264 standard.