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dc.contributor.authorBjorgan, Asgeir
dc.contributor.authorRandeberg, Lise Lyngsnes
dc.date.accessioned2015-02-03T10:48:44Z
dc.date.accessioned2016-04-12T13:59:42Z
dc.date.available2015-02-03T10:48:44Z
dc.date.available2016-04-12T13:59:42Z
dc.date.issued2015
dc.identifier.citationSensors 2015, 15(2):3362-3378nb_NO
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/11250/2385332
dc.description.abstractProcessing line-by-line and in real-time can be convenient for some applications of line-scanning hyperspectral imaging technology. Some types of processing, like inverse modeling and spectral analysis, can be sensitive to noise. The MNF (minimum noise fraction) transform provides suitable denoising performance, but requires full image availability for the estimation of image and noise statistics. In this work, a modified algorithm is proposed. Incrementally-updated statistics enables the algorithm to denoise the image line-by-line. The denoising performance has been compared to conventional MNF and found to be equal. With a satisfying denoising performance and real-time implementation, the developed algorithm can denoise line-scanned hyperspectral images in real-time. The elimination of waiting time before denoised data are available is an important step towards real-time visualization of processed hyperspectral data. The source code can be found at http://www.github.com/ntnu-bioopt/mnf. This includes an implementation of conventional MNF denoising.nb_NO
dc.language.isoengnb_NO
dc.publisherMDPInb_NO
dc.relation.urihttp://www.mdpi.com/1424-8220/15/2/3362
dc.rightsNavngivelse 3.0 Norge*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/no/*
dc.titleReal-Time Noise Removal for Line-Scanning Hyperspectral Devices Using a Minimum Noise Fraction-Based Approachnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.date.updated2015-02-03T10:48:44Z
dc.source.volume15nb_NO
dc.source.journalSensorsnb_NO
dc.source.issue2nb_NO
dc.identifier.doi10.3390/s150203362
dc.identifier.cristin1216144
dc.relation.projectEU/305760nb_NO
dc.description.localcodeThis is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.nb_NO


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