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dc.contributor.authorAkçay, H. Gokhanen_US
dc.contributor.authorAksoy, Selimen_US
dc.coverage.spatialVancouver, BC, Canadaen_US
dc.date.accessioned2016-02-08T12:17:40Z
dc.date.available2016-02-08T12:17:40Z
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/11693/28331
dc.descriptionDate of Conference: 24-29 July 2011en_US
dc.description.abstractWe describe a new procedure that combines statistical and structural characteristics of simple primitive objects to discover compound structures in images. The statistical information that is modeled using spectral, shape, and position data of individual objects, and structural information that is modeled in terms of spatial alignments of neighboring object groups are encoded in a graph structure that contains the primitive objects at its vertices, and the edges connect the potentially related objects. Experiments using WorldView-2 data show that hierarchical clustering of these vertices can find high-level compound structures that cannot be obtained using traditional techniques. © 2011 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.title2011 IEEE International Geoscience and Remote Sensing Symposiumen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/IGARSS.2011.6049690en_US
dc.subjectalignment detectionen_US
dc.subjectgraph-based representationen_US
dc.subjecthierarchical clusteringen_US
dc.subjectObject detectionen_US
dc.subjectCompound structuresen_US
dc.subjectGraph structuresen_US
dc.subjectGraph-based representationsen_US
dc.subjectHier-archical clusteringen_US
dc.subjectIndividual objectsen_US
dc.subjectObject Detectionen_US
dc.subjectObject groupsen_US
dc.subjectPosition dataen_US
dc.subjectSpatial alignmenten_US
dc.subjectStatistical informationen_US
dc.subjectStructural characteristicsen_US
dc.subjectStructural featureen_US
dc.subjectStructural informationen_US
dc.subjectTraditional techniquesen_US
dc.subjectAlignmenten_US
dc.subjectRemote sensingen_US
dc.subjectGeologyen_US
dc.titleDetection of compound structures using hierarchical clustering of statistical and structural featuresen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage2385en_US
dc.citation.epage2388en_US
dc.identifier.doi10.1109/IGARSS.2011.6049690en_US
dc.publisherIEEEen_US


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