A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding

TL;DR

This paper introduces a Bayesian inference model for AV1 video encoding that improves speed with minimal bitrate increase by estimating block structures and optimizing the rate-distortion process.

Contribution

It presents a novel Bayesian block structure inference method tailored for AV1 encoding, enhancing speed and flexibility over existing algorithms.

Findings

Achieves an average of 36.1% time saving in encoding.

Maintains negligible bitrate increase.

Provides flexible control over speed and efficiency tradeoff.

Abstract

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.