Fast entropy-based CABAC rate estimation for mode decision in HEVC

Wei-Gang Chen, Xun Wang

High efficiency video coding (HEVC) seeks the best code tree configuration, the best prediction unit division and the prediction mode, by evaluating the rate-distortion functional in a recursive way and using a "try all and select the best" strategy. Further, HEVC only supports context adaptive binary arithmetic coding (CABAC), which has the disadvantage of being highly sequential and having strong data dependencies, as the entropy coder. So, the development of a fast rate estimation algorithm for CABAC-based coding has a great practical significance for mode decision in HEVC. There are three elementary steps in CABAC encoding process: binarization, context modeling, and binary arithmetic coding. Typical approaches to fast CABAC rate estimation simplify or eliminate the last two steps, but leave the binarization step unchanged. To maximize the reduction of computational complexity, we propose a fast entropy-based CABAC rate estimator in this paper. It eliminates not only the modeling and the coding steps, but also the binarization step. Experimental results demonstrate that the proposed estimator is able to reduce the computational complexity of the mode decision in HEVC by 9-23 % with negligible PSNR loss and BD-rate increment, and therefore exhibits applicability to practical HEVC encoder implementation.