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Multiscale recurrent pattern matching approach for depth map coding

2010-12Conference paper Open access
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorGraziosi, Danillo B.
dc.contributor.authorRodrigues, Nuno M. M.
dc.contributor.authorPagliari, Carla L.
dc.contributor.authorSilva, Eduardo A. B. da
dc.contributor.authorFaria, Sérgio M. M. de
dc.contributor.authorPerez, Marcelo M.
dc.contributor.authorCarvalho, Murilo B. de
dc.date.accessioned2025-10-31T15:58:07Z
dc.date.available2025-10-31T15:58:07Z
dc.date.issued2010-12
dc.descriptionConference date - 8 December 2010 - 10 December 2010; Conference code - 83895
dc.descriptionEISBN - 978-1-4244-7135-5
dc.descriptionFonte: https://www.researchgate.net/publication/220921763_Multiscale_recurrent_pattern_matching_approach_for_depth_map_coding
dc.description.abstractIn this article we propose to compress depth maps using a coding scheme based on multiscale recurrent pattern matching and evaluate its impact on depth image based rendering (DIBR). Depth maps are usually converted into gray scale images and compressed like a conventional luminance signal. However, using traditional transform-based encoders to compress depth maps may result in undesired artifacts at sharp edges due to the quantization of high frequency coefficients. The Multidimensional Multiscale Parser (MMP) is a pattern matching-based encoder, that is able to preserve and efficiently encode high frequency patterns, such as edge information. This ability is critical for encoding depth map images. Experimental results for encoding depth maps show that MMP is much more efficient in a rate-distortion sense than standard image compression techniques such as JPEG2000 or H.264/AVC. In addition, the depth maps compressed with MMP generate reconstructed views with a higher quality than all other tested compression algorithms.eng
dc.description.sponsorshipThis work has been supported by Fundação Para a Ciência e Tecnologia (FCT), under project PTDC/EEA-TEL/099387/2008, the Brazilian Funding Agency FINEP and the Brazilian Army Technological Center.
dc.identifier.citationD. B. Graziosi et al., "Multiscale recurrent pattern matching approach for depth map coding," 28th Picture Coding Symposium, Nagoya, Japan, 2010, pp. 294-297, doi: https://doi.org/10.1109/PCS.2010.5702490.
dc.identifier.doi10.1109/pcs.2010.5702490
dc.identifier.isbn978-1-4244-7134-8
dc.identifier.isbn978-1-4244-7135-5
dc.identifier.urihttp://hdl.handle.net/10400.8/14451
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relationCOMUVI - Compression of Multiview Video
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/5702490
dc.relation.ispartof28th Picture Coding Symposium
dc.rights.uriN/A
dc.subjectDepth Maps
dc.subject3D Image Coding
dc.subjectRecurrent Pattern Matching
dc.titleMultiscale recurrent pattern matching approach for depth map codingeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleCOMUVI - Compression of Multiview Video
oaire.awardURIhttp://hdl.handle.net/10400.8/14449
oaire.citation.conferenceDate2010-12
oaire.citation.conferencePlaceNagoya, Japan
oaire.citation.title28th Picture Coding Symposium, PCS 2010
oaire.fundingStreamConcurso para Projectos de I&D em todos os Domínios Científicos - 2008
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameM. M. Rodrigues
person.familyNameFaria
person.givenNameNuno
person.givenNameSergio
person.identifier.ciencia-id6917-B121-4E34
person.identifier.ciencia-id8815-4101-28DD
person.identifier.orcid0000-0001-9536-1017
person.identifier.orcid0000-0002-0993-9124
person.identifier.ridC-5245-2011
person.identifier.scopus-author-id7006052345
person.identifier.scopus-author-id14027853900
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In this article we propose to compress depth maps using a coding scheme based on multiscale recurrent pattern matching and evaluate its impact on depth image based rendering (DIBR). Depth maps are usually converted into gray scale images and compressed like a conventional luminance signal. However, using traditional transform-based encoders to compress depth maps may result in undesired artifacts at sharp edges due to the quantization of high frequency coefficients. The Multidimensional Multiscale Parser (MMP) is a pattern matching-based encoder, that is able to preserve and efficiently encode high frequency patterns, such as edge information. This ability is critical for encoding depth map images. Experimental results for encoding depth maps show that MMP is much more efficient in a rate-distortion sense than standard image compression techniques such as JPEG2000 or H.264/AVC. In addition, the depth maps compressed with MMP generate reconstructed views with a higher quality than all other tested compression algorithms.
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