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dc.contributor.authorUsakli, Ali Bulent
dc.contributor.authorYavariabdi, Amir
dc.contributor.authorKustogullari, Huseyin
dc.date.accessioned2019-07-09T14:07:52Z
dc.date.available2019-07-09T14:07:52Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/20.500.12498/936
dc.description.abstractThis paper proposes a new unsupervised satellite change de- tection method, which is invariant to shadow and shading e ects. To achieve this, rstly, the RGB satellite images are transformed into spher- ical colour space to remove illumination artifacts. Then, a new unsuper- vised change detection is used. The resultant optimal binary change mask is obtained by minimisation a mean square error based cost function us- ing Binary Particle Swarm Optimisation (BPSO). The proposed method is compared with three other satellite change detection methods and the results demonstrate that our method provides a signi cant improvement of obtaining the changed and unchanged regions on the diference image. The total errors show that our method at least 39.62% better than the best compared method and are utmost 176.18% better than the worst one.en_US
dc.language.isoen_USen_US
dc.subjectRemote sensingen_US
dc.subjectchange detectionen_US
dc.subjectspherical coordinate systemen_US
dc.subjectoptimisationen_US
dc.subjectbinary particle swarm optimisationen_US
dc.titleUnsupervised Satellite Change Detection Using Particle Swarm Optimisation in Spherical Coordinatesen_US
dc.typeConference Paperen_US


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