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dc.contributor.authorDoulgeris, Anthony Paul
dc.contributor.authorCristea, Anca
dc.date.accessioned2019-04-12T10:54:47Z
dc.date.available2019-04-12T10:54:47Z
dc.date.issued2018-11-05
dc.description.abstractWe present a new approach for incorporating incidence angle derived synthetic aperture radar (SAR) brightness variation directly into SAR image analysis. This approach is unique in that the incidence angle dependency is modeled explicitly into the probability density function rather than an image-wide pre-processing `correction'. It can then be used for supervised and unsupervised image analysis, and is notably able to account for a different dependency rate for each class. This has potential benefits for wide-swath SAR imagery over flat areas and ocean, wide angled airborne and UAV based SAR data, connecting narrow-beam SAR images at different acquisition angles, as well as land-based analysis with local topographic terrain angles. An initial example demonstrates unsupervised image segmentation applied to sea ice mapping for meteorological services and climate science, and is compared to the same algorithm without the incidence angle modeling.en_US
dc.description.sponsorshipAkademiaavtale between Statoil and the Arctic University of Norway CIRFA partnersen_US
dc.descriptionAccepted manuscript version. Published version available at <a href=https://doi.org/10.1109/IGARSS.2018.8519043>https://doi.org/10.1109/IGARSS.2018.8519043. </a>en_US
dc.identifier.citationDoulgeris, A.P. & Cristea, A. (2018). Incorporating incidence angle variation into sar image segmentation. <i>IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 22. - 27. July 2018</i>, 8543-8546. https://doi.org/10.1109/IGARSS.2018.8519043en_US
dc.identifier.cristinIDFRIDAID 1667353
dc.identifier.doi10.1109/IGARSS.2018.8519043
dc.identifier.issn2153-6996
dc.identifier.issn2153-7003
dc.identifier.urihttps://hdl.handle.net/10037/15198
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.journalIEEE International Geoscience and Remote Sensing Symposium proceedings
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectSynthetic Aperture Radaren_US
dc.subjectIncidence Angle Correctionen_US
dc.subjectWide-swath imageryen_US
dc.subjectTerrain Correctionen_US
dc.subjectSentinel-1 1en_US
dc.subjectVDP::Mathematics and natural science: 400::Physics: 430en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Fysikk: 430en_US
dc.titleIncorporating Incidence Angle Variation into Sar Image Segmentationen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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