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Titel: INCEPT: Intra CU Depth Prediction for HEVC
Untertitel:
Kurzfassung:

High Efficiency Video Coding (HEVC) improves the encoding efficiency by utilizing sophisticated tools such as flexible Coding Tree Units (CTUs) partitioning. The Coding Units (CUs) can be split recursively into four equally sized CUs ranging from 64×64 to 8×8 pixels. At each depth level (or CU size), intra prediction via exhaustive mode search was exploited in HEVC to improve the encoding efficiency and result in a very high encoding time complexity. This paper proposes an Intra CU Depth Prediction (INCEPT) algorithm, which limits Rate-Distortion Optimization (RDO) for each CTU in HEVC by utilizing the spatial correlation with the neighboring CTUs, which is computed using a DCT energy-based feature. Thus, INCEPT reduces the number of candidate CU sizes required to be considered for each CTU in HEVC intra coding. Experimental results show that the INCEPT algorithm achieves a better trade-off between the encoding efficiency and encoding time saving (i.e., BDR/∆T) than the benchmark algorithms. While BDR/∆T is 12.35% and 9.03% for the benchmark algorithms, it is 5.49% for the proposed algorithm. As a result, INCEPT achieves a 23.34% reduction in encoding time on average while incurring only a 1.67% increase in bitrate than the original coding in the x265 HEVC open-source encoder.

Schlagworte: HEVC, Intra coding, CTU, CU, depth decision
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 06.10.2021 (Print)
Erschienen in: MMSP 2021 Proceedings of the IEEE 23rd International Workshop on Multimedia Signal Processing
MMSP 2021 Proceedings of the IEEE 23rd International Workshop on Multimedia Signal Processing
zur Publikation
 ( IEEE; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 1 - 6

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Erscheinungsdatum: 06.10.2021
ISBN:
  • 978-1-6654-3287-0
ISSN: 2163-3517
Homepage: https://ieeexplore.ieee.org/document/9733517
Erscheinungsdatum: 16.03.2022
ISBN (e-book):
  • 978-1-6654-3288-7
eISSN: 2473-3628
DOI: http://dx.doi.org/10.1109/mmsp53017.2021.9733517
Homepage: https://ieeexplore.ieee.org/document/9733517
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Multimedia Communication

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Beiträge der Publikation

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