Fast Coding Unit Encoding Scheme for HEVC Using Genetic Algorithm

Tun, EE; Aramvith, S; Miyanaga, Y

Fast Coding Unit Encoding Scheme for HEVC Using Genetic Algorithm

Tun, EE Aramvith, S Miyanaga, Y

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Access, 2019, 7, pp. 68010-68021
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Tun, EE
dc.contributor.author	Aramvith, S
dc.contributor.author	Miyanaga, Y https://orcid.org/0000-0002-2795-2234
dc.date.accessioned	2022-09-01T02:59:02Z
dc.date.available	2022-09-01T02:59:02Z
dc.date.issued	2019-01-01
dc.identifier.citation	IEEE Access, 2019, 7, pp. 68010-68021
dc.identifier.issn	2169-3536
dc.identifier.issn	2169-3536
dc.identifier.uri	http://hdl.handle.net/10453/161163
dc.description.abstract	High efficiency video coding (HEVC) is the newest video codec to increase significantly the coding efficiency of its ancestor H.264/Advance Video Coding with the aids of its new features, such as the quadtree-based coding unit partitioning, a simple deblocking filter, and other advanced coding techniques. However, the HEVC delivers a highly increased computation complexity, which is mainly due to the exhaustive rate distortion optimization search of quadtree-based coding unit partitioning. In this paper, a coding unit partitioning pattern optimization method based on a genetic algorithm is proposed to save the computational complexity of hierarchical quadtree-based coding unit partitioning. The required coding unit partitioning pattern for exhaustive partitioning and the rate distortion cost are efficiently considered as the chromosome and the fitness function of the genetic algorithm, respectively. To reduce the computational time, coding unit partitioning patterns of the key frame are searched and shared to other consecutive frames by taking into account the highly temporal correlation. Our evaluation results show that the proposed method can achieve 62.5% and 16.7% computational complexity reduction on average with a negligible average quality degradation compared with HM16.5 and state-of-the-art support vector machine-based fast algorithm, respectively, under low-delay P configuration with rate control while 64.1% and 15.1% under low-delay configuration with rate control.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation	Japan Society for the Promotion of Science18KK0277
dc.relation	Japan Society for the Promotion of Science18H03212
dc.relation.ispartof	IEEE Access
dc.relation.isbasedon	10.1109/ACCESS.2019.2918508
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 10 Technology
dc.title	Fast Coding Unit Encoding Scheme for HEVC Using Genetic Algorithm
dc.type	Journal Article
utslib.citation.volume	7
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	10 Technology
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-09-01T02:58:34Z
pubs.publication-status	Published
pubs.volume	7

Abstract:

High efficiency video coding (HEVC) is the newest video codec to increase significantly the coding efficiency of its ancestor H.264/Advance Video Coding with the aids of its new features, such as the quadtree-based coding unit partitioning, a simple deblocking filter, and other advanced coding techniques. However, the HEVC delivers a highly increased computation complexity, which is mainly due to the exhaustive rate distortion optimization search of quadtree-based coding unit partitioning. In this paper, a coding unit partitioning pattern optimization method based on a genetic algorithm is proposed to save the computational complexity of hierarchical quadtree-based coding unit partitioning. The required coding unit partitioning pattern for exhaustive partitioning and the rate distortion cost are efficiently considered as the chromosome and the fitness function of the genetic algorithm, respectively. To reduce the computational time, coding unit partitioning patterns of the key frame are searched and shared to other consecutive frames by taking into account the highly temporal correlation. Our evaluation results show that the proposed method can achieve 62.5% and 16.7% computational complexity reduction on average with a negligible average quality degradation compared with HM16.5 and state-of-the-art support vector machine-based fast algorithm, respectively, under low-delay P configuration with rate control while 64.1% and 15.1% under low-delay configuration with rate control.

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http://hdl.handle.net/10453/161163