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Motion estimation with chessboard pattern prediction strategy

dc.contributor.authorAmirpour, Hadi
dc.contributor.authorGhanbari, Mohammad
dc.contributor.authorPinheiro, Antonio M. G.
dc.contributor.authorPereira, Manuela
dc.date.accessioned2020-02-13T12:06:53Z
dc.date.available2020-02-13T12:06:53Z
dc.date.issued2019
dc.description.abstractDue to high correlations among the adjacent blocks, several algorithms utilize movement information of spatially and temporally correlated neighboring blocks to adapt their search patterns to that information. In this paper, this information is used to define a dynamic search pattern. Each frame is divided into two sets, black and white blocks, like a chessboard pattern and a different search pattern, is defined for each set. The advantage of this definition is that the number of spatially neighboring blocks is increased for each current block and it leads to a better prediction for each block. Simulation results show that the proposed algorithm is closer to the Full-Search algorithm in terms of quality metrics such as PSNR than the other state-of-the-art algorithms while at the same time the average number of search points is less.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doihttps://doi.org/10.1007/s11042-019-7432-8pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/9259
dc.language.isoengpt_PT
dc.subjectVideo compressionpt_PT
dc.subjectMotion estimationpt_PT
dc.subjectDynamic search patternpt_PT
dc.subjectPredictionpt_PT
dc.subjectPSNRpt_PT
dc.titleMotion estimation with chessboard pattern prediction strategypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F50008%2F2013/PT
oaire.citation.titleMultimedia Tools and Applicationspt_PT
oaire.fundingStream5876
person.familyNameAmirpour
person.familyNamePinheiro
person.familyNamePereira
person.givenNameHadi
person.givenNameAntonio
person.givenNameManuela
person.identifier.ciencia-id2218-265E-17D2
person.identifier.ciencia-id0515-7E9C-B97F
person.identifier.orcid0000-0001-9853-1720
person.identifier.orcid0000-0002-5968-9901
person.identifier.orcid0000-0002-8648-6464
person.identifier.ridB-2723-2012
person.identifier.scopus-author-id8420644500
person.identifier.scopus-author-id35248984200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication94e6047a-198a-41bd-bd6c-b0f21708d8f9
relation.isAuthorOfPublicationb89b2bbc-525d-4a6d-8a41-6ad7b81fa511
relation.isAuthorOfPublication.latestForDiscovery94e6047a-198a-41bd-bd6c-b0f21708d8f9
relation.isProjectOfPublication6051e784-a228-452a-ad8e-90f4372bc6bf
relation.isProjectOfPublication.latestForDiscovery6051e784-a228-452a-ad8e-90f4372bc6bf

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