A fast DEA-based intra-coding algorithm for HEVC

As the newest video coding standard, High Efficiency Video Coding (HEVC) greatly enhances the encoding performance of H. 264/AVC. However, HEVC also has high computational complexity, which limits application of this new standard. In this paper, we propose a fast DEA-based intra-coding algorithm, including block partitioning; prediction mode selection and edge offset (EO) class decision algorithms. The idea behind the proposed algorithm is to utilize the texture characteristics of the encoding image, which are quantified by dominant edge assent (DEA) and its distribution, to reduce the decision space. Specifically, for block partitioning, we propose the most possible depth range (MPDR) and employ DEA to determine whether the current coding block can use the MPDR to predict the partitioning depth or not; for intra-prediction mode selection, we use DEA and its distribution to reduce the range of prediction direction; for the EO class decision, we use DEA to determine the EO class of the sample adaptive offset. We integrate the proposed algorithm into the test model HM 13.0 and present a detailed comparative analysis. Experimental results show that the proposed fast DEA-based intra-coding algorithm reduces the computational complexity of HM 13.0 to about 46% in encoding time with 2.08% increases in the Biontegaard-Delta bitrate (BD-rate). Moreover, the proposed algorithm also demonstrates better performance over other state-of-the-art work.