A fast full partitioning algorithm for HEVC-to-VVC video transcoding using Bayesian classifiers

Abstract

The Versatile Video Coding (VVC) standard was released in 2020 to replace the High Efficiency Video Coding (HEVC) standard, making it necessary to convert HEVC encoded content to VCC to exploit its compression performance, which was achieved by using a larger block size of 128 × 128 pixels, among other new coding tools. However, 80.93% of the encoding time is spent on finding a suitable block partitioning. To reduce this time, this proposal presents an HEVC-to-VVC transcoding algorithm focused on accelerating the CTU partitioning decisions. The transcoder takes different information from the input bitstream of HEVC, and feeds it to two Bayes-based models. Experimental results show a time saving in the transcoding process of 45.40%, compared with the traditional cascade transcoder. This time gain has been obtained on average for all test sequences in the Random Access scenario, at the expense of only 1.50% BD-rate.