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dc.contributor.authorAnfinsen, Stian Normann
dc.date.accessioned2016-02-03T14:44:25Z
dc.date.available2016-02-03T14:44:25Z
dc.date.issued2016-02-03
dc.description.abstractA method is presented which uses logarithmic statistics to detect and characterise class mixtures and targets in background clutter in synthetic aperture radar (SAR) images. Mixtures of ground cover types show up as extreme radar texture in statistical analysis of SAR images. Instead of modelling this as a spatially nonstationary radar cross section, this paper demonstrates how a mixture model analysis can be used to characterise the separate components and estimate their mixing proportions.en_US
dc.identifier.urihttps://hdl.handle.net/10037/8425
dc.identifier.urnURN:NBN:no-uit_munin_7996
dc.language.isoengen_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccess
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412en_US
dc.subjectVDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412en_US
dc.titleStatistical Unmixing of SAR Imagesen_US
dc.typePreprinten_US
dc.typeManuskripten_US


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