An Efficient Context Modeling Algorithm for Motion Vectors in CABAC

Context modeling algorithm for motion vectors presented in this paper is an improvement of the current one used in context-based adaptive binary arithmetic coding (CABAC). In our algorithm for coding the vertical motion vector difference (MVD) components, we take advantage of the coded data of the horizontal MVD components as one of the references for context modeling. Moreover, we adopt different schemes according to the encoding partition sizes. For small block sizes, we only consider the correlation among the neighboring blocks. Whereas for large block sizes, we also employ the inter-correlation between the two MVD components in the current block to improve the probability estimation of symbols. These strategies enhance the accuracy of the context model selection in motion vector coding, thus elevate the efficiency of the context-based arithmetic coder. Experimental results show that the proposed algorithm improves compression performance compared to the original CABAC scheme.