High Efficiency Video Coding (HEVC or H.265), the latest international video coding standard, displays a 50% bit rate reduction with nearly equal quality and dramatically higher coding complexity compared with H.264. Unlike other fast algorithms, we first propose an algorithm that combines the CU coding bits with the reduction of unnecessary intra-prediction modes to decrease computational complexity. In this study, we first analyzed the statistical relationship between the best mode and the costs calculated through Rough Mode Decision (RMD) process and proposed an effective mode decision algorithm in intra-mode prediction process. We alleviated the computation difficulty by carrying out the RMD process in two stages, reducing 35 modes down to 11 modes in the first RMD process stage, and adding modes adjacent to the most promising modes selected during the first stage into the second RMD stage. After these two stages, we had two or three modes ready to be used in the rate distortion operation (RDO) process instead of the three or eight in the original HEVC process, which significantly reduced the number of unnecessary candidate modes in the RDO process. We then used the coding bits of the current coding unit (CU) as the main basis for judging its complexity and proposed an early termination method for CU partition based on the number of coding bits of the current CU. Experimental results show that the proposed fast algorithm provides an average time reduction rate of 53% compared to the reference HM-16.12, with only 1.7% Bjontegaard delta rate increase, which is acceptable for Rate-Distortion performance.
In REF , an algorithm that combines CU coding bits with the reduction of unnecessary intra prediction modes was proposed to decrease computational complexity; it provides an average time reduction rate of 53% with only a 1.7% Bjontegaard delta rate (BD rate) increase.
Fast and adaptive mode decision and CU partition early termination algorithm for intra-prediction in HEVC
EURASIP Journal on Image and Video Processing
Computer Science