Adaptive Weighted Averaged Template Matching Prediction for Intra Coding

Template matching (TM) method has been used in video coding to improve the performance of intra prediction by exploiting non-local correlations. One or more blocks, which are selected by matching the block templates, are used to create prediction samples for the target block. Each selected block is a degraded target block superimposed with the noise caused by compression and inner dissimilarities between the blocks. In this paper, an adaptive weighted averaged template matching (AWTM) method is proposed to minimize the noise variance in prediction samples. The prediction samples are generated by weighted average of several selected blocks. The weights are determined according to the correlations adaptively. Furthermore, a novel approach is proposed to integrate the AWTM method into HEVC test model, including a new derivation algorithm of most probable mode (MPM) list and modifications in coding related syntax elements. Our method can achieve 1.05% coding gain on average and up to 4.24% for luminance component under allintra configuration compared to HEVC test model HM16.0.