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hal.structure.identifierMIT media Lab
dc.contributor.authorWETZSTEIN, Gordon
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorIHRKE, Ivo
hal.structure.identifierComputer Science Department [UBC-Computer Science]
dc.contributor.authorHEIDRICH, Wolfgang
dc.date.accessioned2023-05-12T10:21:27Z
dc.date.available2023-05-12T10:21:27Z
dc.date.issued2013
dc.identifier.issn0920-5691
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/181110
dc.description.abstractEnPhotography has been striving to capture an ever increasing amount of visual information in a single image. Digital sensors, however, are limited to recording a small subset of the desired information at each pixel. A common approach to overcoming the limitations of sensing hardware is the optical multiplexing of high-dimensional data into a photograph. While this is a well-studied topic for imaging with color filter arrays, we develop a mathematical framework that generalizes multiplexed imaging to all dimensions of the plenoptic function. This framework unifies a wide variety of existing approaches to analyze and reconstruct multiplexed data in either the spatial or the frequency domain. We demonstrate many practical applications of our framework including high-quality light field reconstruction, the first comparative noise analysis of light field attenuation masks, and an analysis of aliasing in multiplexing applications.
dc.language.isoen
dc.publisherSpringer Verlag
dc.title.enOn Plenoptic Multiplexing and Reconstruction
dc.typeArticle de revue
dc.subject.halPhysique [physics]/Physique [physics]/Optique [physics.optics]
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
dc.subject.halInformatique [cs]/Synthèse d'image et réalité virtuelle [cs.GR]
dc.subject.halInformatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
bordeaux.journalInternational Journal of Computer Vision
bordeaux.page384--400
bordeaux.volume101
bordeaux.hal.laboratoriesLaboratoire Photonique, Numérique et Nanosciences (LP2N) - UMR 5298*
bordeaux.issue2
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-00876493
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00876493v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=International%20Journal%20of%20Computer%20Vision&rft.date=2013&rft.volume=101&rft.issue=2&rft.spage=384--400&rft.epage=384--400&rft.eissn=0920-5691&rft.issn=0920-5691&rft.au=WETZSTEIN,%20Gordon&IHRKE,%20Ivo&HEIDRICH,%20Wolfgang&rft.genre=article


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