VLC table prediction for CAVLC in H.264/AVC using correlation, statistics, and structural characteristics of mode information

The H.264/AVC video coding standard adopted context-based adaptive variable length coding (CAVLC) as an entropy coding tool. By combining adaptive variable length coding (VLC) with context modeling, we can achieve a high coding performance. However, CAVLC in H.264/AVC has the problem that VLC table prediction is not always accurate. In this paper, we propose a new VLC table prediction algorithm using the correlation between coding modes of the current and neighboring sub-blocks and the statistics of mode distribution in both intra and inter frames. In addition, we can further increase correctness of VLC table prediction considering the structural characteristics of mode information in inter frames. Experimental results show that the proposed algorithm increases correctness of VLC table prediction by 10.07% and reduces the bit rate by 1.21% on average without significant increment of encoding time.