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dc.contributor.authorSchambach, Maximilian
dc.date.accessioned2022-10-25T09:32:05Z
dc.date.available2022-10-25T09:32:05Z
dc.date.issued2022
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/59047
dc.description.abstractIn this work, spatio-spectrally coded multispectral light fields, as taken by a light field camera with a spectrally coded microlens array, are investigated. For the reconstruction of the coded light fields, two methods, one based on the principles of compressed sensing and one deep learning approach, are developed. Using novel synthetic as well as a real-world datasets, the proposed reconstruction approaches are evaluated in detail.en_US
dc.languageEnglishen_US
dc.relation.ispartofseriesForschungsberichte aus der Industriellen Informationstechniken_US
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineeringen_US
dc.subject.otherComputer Vision; Lichtfelder; Multispektrale Bildgebung; Compressed Sensing; Deep Learning; computer vision; light fields; multispectral imaging; compressed sensing; deep learningen_US
dc.titleReconstruction from Spatio-Spectrally Coded Multispectral Light Fieldsen_US
dc.typebook
oapen.identifier.doi10.5445/KSP/1000148072en_US
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9en_US
oapen.series.number27en_US
oapen.pages238en_US
peerreview.anonymityAll identities known
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.review.stagePre-publication
peerreview.review.typeFull text
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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