research-article

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

Authors:

D. García-Lucas,

G. Cebrián-Márquez,

A.J. Díaz-Honrubia,

T. Mallikarachchi,

P. CuencaAuthors Info & Claims

Volume 94, Issue C

https://doi.org/10.1016/j.jvcir.2023.103829

Published: 01 June 2023 Publication History

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.

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Index Terms

A fast full partitioning algorithm for HEVC-to-VVC video transcoding using Bayesian classifiers
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Journal of Visual Communication and Image Representation

Journal of Visual Communication and Image Representation Volume 94, Issue C

Jun 2023

232 pages

ISSN:1047-3203

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Elsevier Inc.

Publisher

Academic Press, Inc.

United States

Publication History

Published: 01 June 2023

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