Fast HEVC Encoding Decisions Using Data Mining

Correa, Guilherme; Assunção, Pedro; Agostini, Luciano Volcan; Cruz, Luis A. da Silva

Publication

Fast HEVC Encoding Decisions Using Data Mining

2015-04Journal article

datacite.subject.fos	Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg	09:Indústria, Inovação e Infraestruturas
dc.contributor.author	Correa, Guilherme
dc.contributor.author	Assunção, Pedro
dc.contributor.author	Agostini, Luciano Volcan
dc.contributor.author	Cruz, Luis A. da Silva
dc.date.accessioned	2025-07-14T13:48:44Z
dc.date.available	2025-07-14T13:48:44Z
dc.date.issued	2015-04
dc.description	Article number - 6926811
dc.description.abstract	The High Efficiency Video Coding standard provides improved compression ratio in comparison with its predecessors at the cost of large increases in the encoding computational complexity. An important share of this increase is due to the new flexible partitioning structures, namely the coding trees, the prediction units, and the residual quadtrees, with the best configurations decided through an exhaustive rate-distortion optimization (RDO) process. In this paper, we propose a set of procedures for deciding whether the partition structure optimization algorithm should be terminated early or run to the end of an exhaustive search for the best configuration. The proposed schemes are based on decision trees obtained through data mining techniques. By extracting intermediate data, such as encoding variables from a training set of video sequences, three sets of decision trees are built and implemented to avoid running the RDO algorithm to its full extent. When separately implemented, these schemes achieve average computational complexity reductions (CCRs) of up to 50% at a negligible cost of 0.56% in terms of Bjontegaard Delta (BD) rate increase. When the schemes are jointly implemented, an average CCR of up to 65% is achieved, with a small BD-rate increase of 1.36%. Extensive experiments and comparisons with similar works demonstrate that the proposed early termination schemes achieve the best rate-distortion-complexity tradeoffs among all the compared works.	eng
dc.description.sponsorship	Funding Agency: Brazilian Agency for Scientific and Technological Development, Brazil National Council for the Improvement of Higher Education, Brazil Foundation for Science and Technology (Grant Number: FCT/1909/27/2/2014/S)
dc.identifier.citation	G. Correa, P. A. Assuncao, L. V. Agostini and L. A. da Silva Cruz, "Fast HEVC Encoding Decisions Using Data Mining," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 4, pp. 660-673, April 2015, doi: 10.1109/TCSVT.2014.2363753.
dc.identifier.doi	10.1109/tcsvt.2014.2363753
dc.identifier.issn	1051-8215
dc.identifier.issn	1558-2205
dc.identifier.uri	http://hdl.handle.net/10400.8/13623
dc.language.iso	eng
dc.peerreviewed	yes
dc.publisher	IEEE
dc.relation.hasversion	https://ieeexplore.ieee.org/document/6926811
dc.relation.ispartof	IEEE Transactions on Circuits and Systems for Video Technology
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject	decision trees
dc.subject	Early termination
dc.subject	high efficiency video coding (HEVC)
dc.title	Fast HEVC Encoding Decisions Using Data Mining	eng
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.endPage	673
oaire.citation.issue	4
oaire.citation.startPage	660
oaire.citation.title	IEEE Transactions on Circuits and Systems for Video Technology
oaire.citation.volume	25
oaire.version	http://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyName	Assunção
person.givenName	Pedro
person.identifier.ciencia-id	6811-3984-C17B
person.identifier.orcid	0000-0001-9539-8311
person.identifier.rid	A-4827-2017
person.identifier.scopus-author-id	6701838347
relation.isAuthorOfPublication	25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication.latestForDiscovery	25649bb9-f135-48e8-8d0f-3706b86701d3