A Conditional Bayesian Block Structure Inference Model for Optimized AV1 Encoding

AV1, a next-generation open-source and royalty-free video coding standard, achieves high compression performance at high computational cost. To meet the requirements of HD and UHD video applications, extensive optimizations in both the algorithm and implementation of AV1 are required. In this paper, we analyze the similarities between the block structure decisions after rate-distortion (RD) optimized AV1 and HEVC encodings of the same input. Taking advantage of such similarities, we propose a conditional Bayesian inference model to perform early termination in block partition determination of AV1 based on HEVC encoding outputs. An estimation algorithm is designed to iteratively calculate the prior probability for Bayesian inference. Experiment results show that our proposed algorithm could realize an average time saving of 35.7% and negligible BD-rate loss (0.61%), with the pre-encoding time taken into consideration.