A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding
This addresses a specific bottleneck in video encoding for AV1 users, though it appears incremental as it modifies an existing HEVC-based approach.
The paper tackles the problem of adapting multi-rate video encoding to AV1's special reference frames without significant rate-distortion loss by proposing a Bayesian block structure inference model. The method achieves an average time saving of 36.1% (up to 50.6%) with negligible bitrate cost.
Due to differences in frame structure, existing multi-rate video encoding algorithms cannot be directly adapted to encoders utilizing special reference frames such as AV1 without introducing substantial rate-distortion loss. To tackle this problem, we propose a novel bayesian block structure inference model inspired by a modification to an HEVC-based algorithm. It estimates the posterior probabilistic distributions of block partitioning, and adapts early terminations in the RDO procedure accordingly. Experimental results show that the proposed method provides flexibility for controlling the tradeoff between speed and coding efficiency, and can achieve an average time saving of 36.1% (up to 50.6%) with negligible bitrate cost.