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hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
hal.structure.identifierImagine Optic
dc.contributor.authorHERZOG, Charlotte
hal.structure.identifierImagine Optic
dc.contributor.authorDOVILLAIRE, Guillaume
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
dc.contributor.authorGRANIER, Xavier
hal.structure.identifierImagine Optic
dc.contributor.authorHARMS, Fabrice
hal.structure.identifierImagine Optic
dc.contributor.authorLEVECQ, Xavier
hal.structure.identifierLaboratoire d'optique appliquée [LOA]
dc.contributor.authorLONGO, Elena
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
dc.contributor.authorMIGNARD-DEBISE, Lois
hal.structure.identifierLaboratoire d'optique appliquée [LOA]
dc.contributor.authorZEITOUN, Philippe
hal.structure.identifierImagine Optic
dc.contributor.authorDE LA ROCHEFOUCAULD, Ombeline
dc.date.accessioned2023-05-12T10:48:44Z
dc.date.available2023-05-12T10:48:44Z
dc.date.conference2018-04-22
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/181778
dc.description.abstractEnPlenoptic cameras provide single-shot 3D imaging capabilities, based on the acquisition of the Light-Field, which corresponds to a spatial and directional sampling of all the rays of a scene reaching a detector. Specific algorithms applied on raw Light-Field data allow for the reconstruction of an object at different depths of the scene.Two different plenoptic imaging geometries have been reported, associated with two reconstruction algorithms: the traditional or unfocused plenoptic camera, also known as plenoptic camera 1.0, and the focused plenoptic camera, also called plenoptic camera 2.0. Both systems use the same optical elements, but placed at different locations: a main lens, a microlens array and a detector. These plenoptic systems have been presented as independent. Here we show the continuity between them, by simply moving the position of an object. We also compare the two reconstruction methods. We theoretically show that the two algorithms are intrinsically based on the same principle and could be applied to any Light-Field data. However, the resulting images resolution and quality depend on the chosen algorithm.
dc.language.isoen
dc.publisherSPIE
dc.subject.enImage resolution
dc.subject.enImage quality
dc.subject.enData acquisition
dc.subject.enPlenoptic imaging
dc.subject.enUnfocused Light-Field Camera
dc.subject.enFocused Light-Field Camera
dc.subject.enDetection and tracking algorithms
dc.subject.enReconstruction algorithm
dc.subject.enMicrolens array
dc.subject.enReconstruction algorithms
dc.subject.enMicrolens
dc.subject.enCameras
dc.subject.enSensors
dc.subject.enImaging systems
dc.subject.enRefocusing
dc.title.enComparison of reconstruction approaches for plenoptic imaging systems
dc.typeCommunication dans un congrès avec actes
dc.identifier.doi10.1117/12.2306800
dc.subject.halSciences de l'ingénieur [physics]/Optique / photonique
dc.description.sponsorshipEuropevolumetric medical x-ray imaging at extremely low dose
bordeaux.page106772U:1-106772U:11
bordeaux.volume10677
bordeaux.hal.laboratoriesLaboratoire Photonique, Numérique et Nanosciences (LP2N) - UMR 5298*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.countryFR
bordeaux.title.proceedingUnconventional Optical Imaging
bordeaux.conference.cityStrasbourg
bordeaux.peerReviewedoui
hal.identifierhal-01819610
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01819610v1
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