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Light Field Disparity Map Enhancement with Morphological Filtering

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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorLourenco, Rui
dc.contributor.authorThomaz, Lucas A.
dc.contributor.authorSilva, Eduardo A. B. da
dc.contributor.authorAssuncao, Pedro A. A.
dc.contributor.authorTavora, Luis M. N.
dc.contributor.authorFaria, Sergio M. M. de
dc.date.accessioned2026-03-16T15:40:32Z
dc.date.available2026-03-16T15:40:32Z
dc.date.issued2021-02
dc.descriptionDate of Conference: 11-12 February 2021
dc.descriptionEISBN - 978-1-6654-1588-0
dc.description.abstractLight field disparity estimation algorithms are comprised of two steps: an initial estimation step and a global optimization step. The initial estimation is often noisy and may contain high amplitude artefacts. Global optimization techniques might inadequately propagate these artefacts, providing suboptimal results. In this paper, an iterative morphological filter is proposed as an intermediate step or replacement to global optimization techniques. This algorithm iteratively filters the disparity map with an average of Open followed by Close and Close followed by Open morphological operations, enabling the removal of artefacts and noise, without adversely affecting the structure of the disparity map. The iterative open-close close-open filter attenuates the effect of artefacts and noise from an initial disparity estimation, achieving improvements of up to 90%, and more than 30%, on average, in terms of mean square error, when applied to the a structure-tensor-based initial estimation. In addition, the proposed method proves to be competitive with another state of the art algorithm, in terms of mean square error, and superior in terms of percentage of bad pixels.eng
dc.description.sponsorshipThis work was supported by Programa Operacional Regional do Centro, project PLenoISLA POCI-01-0145-FEDER-028325 and by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/EEA/50008/2020, Portugal.
dc.identifier.citationR. Lourenco, L. A. Thomaz, E. A. B. da Silva, P. A. A. Assuncao, L. M. N. Tavora and S. M. M. de Faria, "Light Field Disparity Map Enhancement with Morphological Filtering," 2021 Telecoms Conference (ConfTELE), Leiria, Portugal, 2021, pp. 1-6, doi: https://doi.org/10.1109/ConfTELE50222.2021.9435594.
dc.identifier.doi10.1109/conftele50222.2021.9435594
dc.identifier.isbn978-1-6654-4680-8
dc.identifier.isbn978-1-6654-1588-0
dc.identifier.urihttp://hdl.handle.net/10400.8/15884
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/9435594
dc.relation.ispartof2021 Telecoms Conference (ConfTELE)
dc.rights.uriN/A
dc.subjectLight Field
dc.subjectDisparity
dc.subjectMorphological Operation
dc.titleLight Field Disparity Map Enhancement with Morphological Filteringeng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2021-02
oaire.citation.conferencePlaceLeiria, Portugal
oaire.citation.title2021 Telecoms Conference, ConfTELE 2021
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameThomaz
person.familyNameAssunção
person.familyNamede Oliveira Pegado de Noronha E Távora
person.familyNameFaria
person.givenNameLucas
person.givenNamePedro
person.givenNameLuís Miguel
person.givenNameSergio
person.identifier.ciencia-id6811-3984-C17B
person.identifier.ciencia-id121C-FADA-D750
person.identifier.ciencia-id8815-4101-28DD
person.identifier.orcid0000-0002-1004-7772
person.identifier.orcid0000-0001-9539-8311
person.identifier.orcid0000-0002-8580-1979
person.identifier.orcid0000-0002-0993-9124
person.identifier.ridA-4827-2017
person.identifier.ridC-5245-2011
person.identifier.scopus-author-id6701838347
person.identifier.scopus-author-id14027853900
relation.isAuthorOfPublication5aaecc29-3e2f-49a6-9fd9-7000d9f6085f
relation.isAuthorOfPublication25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication71940f24-f333-4ab6-abf6-00c7119a07c2
relation.isAuthorOfPublicationf69bd4d6-a6ef-4d20-8148-575478909661
relation.isAuthorOfPublication.latestForDiscovery5aaecc29-3e2f-49a6-9fd9-7000d9f6085f

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Light field disparity estimation algorithms are comprised of two steps: an initial estimation step and a global optimization step. The initial estimation is often noisy and may contain high amplitude artefacts. Global optimization techniques might inadequately propagate these artefacts, providing suboptimal results. In this paper, an iterative morphological filter is proposed as an intermediate step or replacement to global optimization techniques. This algorithm iteratively filters the disparity map with an average of Open followed by Close and Close followed by Open morphological operations, enabling the removal of artefacts and noise, without adversely affecting the structure of the disparity map. The iterative open-close close-open filter attenuates the effect of artefacts and noise from an initial disparity estimation, achieving improvements of up to 90%, and more than 30%, on average, in terms of mean square error, when applied to the a structure-tensor-based initial estimation. In addition, the proposed method proves to be competitive with another state of the art algorithm, in terms of mean square error, and superior in terms of percentage of bad pixels.
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