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dc.contributor.authorAksoy, Selimen_US
dc.contributor.authorAkçay H. Gökhanen_US
dc.coverage.spatialIstanbul, Turkey
dc.date.accessioned2016-02-08T11:49:56Z
dc.date.available2016-02-08T11:49:56Z
dc.date.issued2005-06en_US
dc.identifier.urihttp://hdl.handle.net/11693/27292
dc.descriptionDate of Conference: 9-11 June 2005
dc.descriptionConference name: Proceedings of 2nd International Conference on Recent Advances in Space Technologies, 2005. RAST 2005.
dc.description.abstractWe present an approach for classification of remotely sensed imagery using spatial information extracted from multi-resolution approximations. The wavelet transform is used to obtain multiple representations of an image at different resolutions to capture different details inherently found in different structures. Then, pixels at each resolution are grouped into contiguous regions using clustering and mathematical morphology-based segmentation algorithms. The resulting regions are modeled using the statistical summaries of their spectral, textural and shape properties. These models are used to cluster the regions, and the cluster memberships assigned to each region in multiple resolution levels are used to classify the corresponding pixels into land cover/land use categories. Final classification is done using decision tree classifiers. Experiments with two ground truth data sets show the effectiveness of the proposed approach over traditional techniques that do not make strong use of region-based spatial information. © 2005 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleRAST 2005 - Proceedings of 2nd International Conference on Recent Advances in Space Technologiesen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/RAST.2005.1512638en_US
dc.subjectAlgorithmsen_US
dc.subjectImage resolutionen_US
dc.subjectImage segmentationen_US
dc.subjectPixelsen_US
dc.subjectRemote sensingen_US
dc.subjectStatistical methodsen_US
dc.subjectWavelet transformsen_US
dc.subjectMulti resolution approximationen_US
dc.subjectMulti resolution segmentationen_US
dc.subjectSegmentation algorithmsen_US
dc.subjectImage classificationen_US
dc.titleMulti-resolution segmentation and shape analysis for remote sensing image classificationen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage599en_US
dc.citation.epage604en_US
dc.identifier.doi10.1109/RAST.2005.1512638en_US
dc.publisherIEEE


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