Target detection and classification in SAR images using region covariance and co-difference

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.contributor.authorDuman, Kaanen_US
dc.contributor.authorEryıldırım, Abdulkadiren_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialOrlando, Florida, United States
dc.date.accessioned2016-02-08T11:34:24Z
dc.date.available2016-02-08T11:34:24Z
dc.date.issued2009-04en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 13-17 April 2009
dc.descriptionConference name: SPIE Defense, Security, and Sensing, 2009 - Proceedings - Algorithms for Synthetic Aperture Radar Imagery XVI
dc.description.abstractIn this paper, a novel descriptive feature parameter extraction method from synthetic aperture radar (SAR) images is proposed. The new approach is based on region covariance (RC) method which involves the computation of a covariance matrix whose entries are used in target detection and classification. In addition the region co-difference matrix is also introduced. Experimental results of object detection in MSTAR (moving and stationary target recognition) database are presented. The RC and region co-difference method delivers high detection accuracy and low false alarm rates. It is also experimentally observed that these methods produce better results than the commonly used principal component analysis (PCA) method when they are used with different distance metrics introduced. © 2009 SPIE.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:34:24Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2009en
dc.identifier.doi10.1117/12.818725en_US
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/11693/26739
dc.language.isoEnglishen_US
dc.publisherSPIE
dc.relation.isversionofhttp://dx.doi.org/10.1117/12.818725en_US
dc.source.titleProceedings of SPIE - Algorithms for Synthetic Aperture Radar Imagery XVIen_US
dc.subjectAutomatic target recognition (ATR) and classificationen_US
dc.subjectPrincipal component analysis (PCA)en_US
dc.subjectRegion co-difference matrixen_US
dc.subjectRegion covariance (RC)en_US
dc.subjectSynthetic aperture radar (SAR) imagesen_US
dc.subjectDetection accuracyen_US
dc.subjectDifference matrixen_US
dc.subjectDifference methoden_US
dc.subjectDistance metricsen_US
dc.subjectFalse alarm rateen_US
dc.subjectFeature parametersen_US
dc.subjectNew approachesen_US
dc.subjectObject Detectionen_US
dc.subjectSAR Imagesen_US
dc.subjectStationary targetsen_US
dc.subjectSynthetic aperture radar imagesen_US
dc.subjectTarget detectionen_US
dc.subjectAutomatic target recognitionen_US
dc.subjectCovariance matrixen_US
dc.subjectFeature extractionen_US
dc.subjectImage classificationen_US
dc.subjectImaging systemsen_US
dc.subjectObject recognitionen_US
dc.subjectParameter extractionen_US
dc.subjectPhotoacoustic effecten_US
dc.subjectPrincipal component analysisen_US
dc.subjectRadaren_US
dc.subjectRadar antennasen_US
dc.subjectRadar imagingen_US
dc.subjectSynthetic aperture radaren_US
dc.subjectSynthetic aperturesen_US
dc.subjectTarget dronesen_US
dc.subjectTarget trackingen_US
dc.subjectTargetsen_US
dc.subjectTracking radaren_US
dc.subjectRadar target recognitionen_US
dc.titleTarget detection and classification in SAR images using region covariance and co-differenceen_US
dc.typeConference Paperen_US

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