Context adaptive mode sorting for fast HEVC mode decision

Typical H.265/High Efficiency Video Coding (HEVC) encoder implementations test a variety of prediction modes and select the optimal configuration for each block in terms of Rate-Distortion (RD) cost. A fast HEVC mode decision algorithm is proposed here referred to as Context Adaptive Mode Sorting (CAMS). The frequency of selection of modes and their RD costs are collected while encoding the training frames based on local parameters (the context). This information is then used to sort and restrict the prediction modes to test for each context, while the optimal mode found using CAMS on each CU is validated based on the RD cost distributions found during the training. Experimental results show that the method reduces total encoding time of fast HEVC implementations on average by 29.3%, at modest efficiency losses.