Master data

Title: All-Intra Rate Control Using Low Complexity Video Features for Versatile Video Coding
Subtitle:
Abstract:

Versatile Video Coding (VVC) allows for large compression efficiency gains over its predecessor, High Efficiency Video Coding (HEVC). The added efficiency comes at the cost of increased runtime complexity, especially for encoding. It is thus highly relevant to explore all available runtime reduction options. This paper proposes a novel first pass for two-pass rate control in all-intra configuration, using low-complexity video analysis and a Random Forest (RF)-based machine learning model to derive the data required for driving the second pass. The proposed method is validated using VVenC, an open and optimized VVC encoder. Compared to the default two-pass rate control algorithm in VVenC, the proposed method achieves around 32% reduction in encoding time for the preset faster, while on average only causing 2% BD-rate increase and achieving similar rate control accuracy.

Keywords: Rate control, Complexity reduction, Random Forest, Machine learning, VVC
Publication type: Article in Proceedings (Authorship)
Publication date: 08.10.2023 (Print)
Published by: ICIP '23 Proceedings of the IEEE International Conference on Image Processing
ICIP '23 Proceedings of the IEEE International Conference on Image Processing
to publication
 ( IEEE Xplore Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 2760 - 2764

Versionen

Keine Version vorhanden
Publication date: 11.09.2023
ISBN (e-book):
  • 978-1-7281-9835-4
eISSN: -
DOI: http://dx.doi.org/10.1109/icip49359.2023.10222792
Homepage: https://ieeexplore.ieee.org/document/10222792
Open access
  • Available online (not open access)
Publication date: 08.10.2023
ISBN:
  • 978-1-7281-9835-4
ISSN: -
Homepage: https://ieeexplore.ieee.org/document/10222792

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Systeme

Cooperations

Organisation Address
Université Paris-Saclay
Discovery - RD 128-2e ét
91190 Saint-Aubin
France
   communication@universite-paris-saclay.fr
https://www.universite-paris-saclay.fr/fr
Discovery - RD 128-2e ét
FR - 91190  Saint-Aubin
Fraunhofer HHI
Einsteinufer 37
10587 Berlin
Germany
Einsteinufer 37
DE - 10587  Berlin

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