Fast Intra Mode Decision Algorithm for Versatile Video Coding

To achieve higher coding efficiency, the latest Versatile Video Coding (VVC) standard adopts a series of new intra coding techniques, including the quadtree plus multi-type tree (QTMT), intra sub-partitions (ISP) and intra block copy (IBC). However, this makes the intra coding more complicated, as VVC needs to traverse all prediction modes and partition types of QTMT to find the optimal combination. In this paper, we propose a fast algorithm for VVC from two aspects of mode selection and prediction terminating to reduce coding complexity. For the mode selection, adaptive mode pruning (AMP) is proposed to remove non-promising modes. First, since the newly introduced modes (IBC and ISP) are not effective for all blocks, learning-based classifiers are designed to remove them intelligently. Second, for normal modes, an ensemble decision strategy is proposed to sort the candidate modes and increase the probability of being the optimal mode for the first few candidates; thus, we can remove redundant candidates more efficiently. In terms of prediction terminating, we find that different optimal modes of current depth level lead to different termination probabilities of remaining intra predictions. Therefore, mode-dependent termination (MDT) is proposed to select an appropriate model through the optimal mode and terminate unnecessary intra predictions of remaining depth levels. The proposed algorithm is implemented on VVC test model, and simulation results show that it can achieve 51%$\sim$53% time savings with only 0.93%$\sim$1.08% BDBR increases.