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dc.contributor.authorDeger, Ferdinand
dc.contributor.authorMansouri, Alamin
dc.contributor.authorPedersen, Marius
dc.contributor.authorHardeberg, Jon Yngve
dc.contributor.authorVoisin, Yvon
dc.date.accessioned2019-11-22T08:03:40Z
dc.date.available2019-11-22T08:03:40Z
dc.date.created2015-07-30T11:39:45Z
dc.date.issued2015
dc.identifier.citationOptics Express. 2015, 23 (3), 1938-1950.nb_NO
dc.identifier.issn1094-4087
dc.identifier.urihttp://hdl.handle.net/11250/2629964
dc.description.abstractMany denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term accounts the structural proposition of a hyperspectral image cube. We evaluate the approach on a synthetic dataset that guarantees a noise-free ground truth, and the best results are achieved when the dark current is taken into account.nb_NO
dc.description.abstractA sensor-data-based denoising framework for hyperspectral imagesnb_NO
dc.language.isoengnb_NO
dc.publisherOptical Society of Americanb_NO
dc.titleA sensor-data-based denoising framework for hyperspectral imagesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber1938-1950nb_NO
dc.source.volume23nb_NO
dc.source.journalOptics Expressnb_NO
dc.source.issue3nb_NO
dc.identifier.doi10.1364/OE.23.001938
dc.identifier.cristin1255728
dc.description.localcodeOpen Accessnb_NO
cristin.unitcode194,0,0,0
cristin.unitcode194,63,10,0
cristin.unitnameNorges teknisk-naturvitenskapelige universitet
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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