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acessibilidade

http://hdl.handle.net/10071/16338
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acessibilidade
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dc.contributor.authorConti, C.-
dc.contributor.authorNunes, P.-
dc.contributor.authorDucla Soares, L.-
dc.date.accessioned2018-07-12T09:07:55Z-
dc.date.available2018-07-12T09:07:55Z-
dc.date.issued2017-
dc.identifier.isbn9781510612495-
dc.identifier.issn0277-7860-
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-39675-
dc.identifier.urihttp://hdl.handle.net/10071/16338-
dc.description.abstractLight field imaging based on a single-tier camera equipped with a microlens array – also known as integral, holoscopic, and plenoptic imaging – has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require developing adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, self-similarity compensated prediction is a non-local spatial prediction scheme based on block matching that has been shown to achieve high efficiency for light field image coding based on the High Efficiency Video Coding (HEVC) standard. As previously shown by the authors, this is possible by simply averaging two predictor blocks that are jointly estimated from a causal search window in the current frame itself, referred to as self-similarity bi-prediction. However, theoretical analyses for motion compensated bi-prediction have suggested that it is still possible to achieve further rate-distortion performance improvements by adaptively estimating the weighting coefficients of the two predictor blocks. Therefore, this paper presents a comprehensive study of the rate-distortion performance for HEVC-based light field image coding when using different sets of weighting coefficients for self-similarity bi-prediction. Experimental results demonstrate that it is possible to extend the previous theoretical conclusions to light field image coding and show that the proposed adaptive weighting coefficient selection leads to up to 5 % of bit savings compared to the previous self-similarity bi-prediction scheme.por
dc.language.isoengpor
dc.publisherSPIEpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147328/PTpor
dc.rightsopenAccesspor
dc.subjectLight field codingpor
dc.subjectPlenopticpor
dc.subjectHoloscopicpor
dc.subjectHEVCpor
dc.subjectWeighted bi-predictionpor
dc.titleWeighted bi-prediction for light field image codingpor
dc.typeconferenceObjecten_US
dc.event.titleApplications of Digital Image Processing XL 2017por
dc.event.typeConferênciapor
dc.publicationstatusPublicadopor
dc.peerreviewedyespor
dc.journalApplications of Digital Image Processing XL 2017en_US
dc.volume10396en_US
degois.publication.locationSan Diegopor
degois.publication.titleApplications of Digital Image Processing XL 2017por
dc.date.updated2018-07-12T09:06:59Z-
dc.description.versioninfo:eu-repo/semantics/acceptedVersion-
dc.identifier.doi10.1117/12.2275056-
Appears in Collections:CTI-CRI - Comunicações a conferências internacionais

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