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dc.contributor.authorAkbari, Vahid
dc.contributor.authorDoulgeris, Anthony Paul
dc.contributor.authorGabriele, Moser
dc.contributor.authorEltoft, Torbjørn
dc.contributor.authorSebastiano, B. Serpico
dc.contributor.authorAnfinsen, Stian Normann
dc.date.accessioned2013-07-05T08:12:05Z
dc.date.available2013-07-05T08:12:05Z
dc.date.issued2013
dc.description.abstractThis paper proposes a novel unsupervised, non-Gaussian, and contextual segmentation method that combines an advanced statistical distribution with spatial contextual informa-tion for multilook polarimetric synthetic aperture radar (PolSAR)data. This extends on previous studies that have shown the added value of both non-Gaussian modeling and contextual smoothing individually or for intensity channels only. The method is based on a Markov random field (MRF) model that integrates a K-Wishart distribution for the PolSAR data statistics conditioned to each im-age cluster and a Potts model for the spatial context. Specifically,the proposed algorithm is constructed based upon the stochastic expectation maximization (SEM) algorithm. A new formulation of SEM is developed to jointly perform clustering of the data and parameter estimation of theK-Wishart distribution and the MRF model. Experiments on simulated and real PolSAR data demonstrate the added value of using an appropriate statistical representation, in combination with contextual smoothingen
dc.descriptionThis article is part of Vahid Akbari's doctoral thesis, available in Munin at <a href=http://hdl.handle.net/10037/5243>http://hdl.handle.net/10037/5243</a>en
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing 51(2013) nr. 4 s. 2442-2453en
dc.identifier.cristinIDFRIDAID 946922
dc.identifier.doihttp://dx.doi.org/10.1109/TGRS.2012.2211367
dc.identifier.issn0196-2892
dc.identifier.urihttps://hdl.handle.net/10037/5251
dc.identifier.urnURN:NBN:no-uit_munin_4969
dc.language.isoengen
dc.publisherIEEE Xploreen
dc.rights.accessRightsopenAccess
dc.subjectVDP::Mathematics and natural science: 400en
dc.subjectVDP::Matematikk og Naturvitenskap: 400en
dc.titleA Textural–Contextual Model for Unsupervised Segmentation of Multipolarization Synthetic Aperture Radar Imagesen
dc.typeJournal articleen
dc.typeTidsskriftartikkelen
dc.typePeer revieweden


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