Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/70868
DC FieldValueLanguage
dc.contributor.authorChang, C.I.en_US
dc.contributor.authorLiu, J.M.en_US
dc.contributor.authorChieu, B.C.en_US
dc.contributor.authorRen, H.en_US
dc.contributor.authorWang, C.M.en_US
dc.contributor.authorLo, C.S.en_US
dc.contributor.authorChung, P.C.en_US
dc.contributor.authorYang, C.W.en_US
dc.contributor.authorMa, D.J.en_US
dc.date2000zh_TW
dc.date.accessioned2014-06-11T06:00:30Z-
dc.date.available2014-06-11T06:00:30Z-
dc.identifier.issn0091-3286zh_TW
dc.identifier.urihttp://hdl.handle.net/11455/70868-
dc.description.abstractSubpixel detection in multispectral imagery presents a challenging problem due to relatively low spatial and spectral resolution. We present a generalized constrained energy minimization (GCEM) approach to detecting targets in multispectral imagery at subpixel level. GCEM is a hybrid technique that combines a constrained energy minimization (CEM) method developed for hyperspectral image classification with a dimensionality expansion (DE) approach resulting from a generalized orthogonal subspace projection (GOSP) developed for multispectral image classification. DE enables us to generate additional bands from original multispectral images nonlinearly so that CEM can be used for subpixel detection to extract targets embedded in multispectral images. CEM has been successfully applied to hyperspectral target detection and image classification. Its applicability to multispectral imagery is yet to be investigated. A potential limitation of CEM on multispectral imagery is the effectiveness of interference elimination due to the lack of sufficient dimensionality. DE is introduced to mitigate this problem by expanding the original data dimensionality. Experiments show that the proposed GCEM detects targets more effectively than GOSP and CEM without dimensionality expansion. (C) 2000 Society of Photo-Optical Instrumentation Engineers.en_US
dc.language.isoen_USzh_TW
dc.relationOptical Engineeringen_US
dc.relation.ispartofseriesOptical Engineering, Volume 39, Issue 5, Page(s) 1275-1281.en_US
dc.relation.urihttp://dx.doi.org/10.1117/1.602486en_US
dc.subjectclassificationen_US
dc.subjectconstrained energy minimizationen_US
dc.subjectdimensionalityen_US
dc.subjectexpansionen_US
dc.subjectgeneralized constrained energy minimizationen_US
dc.subjectgeneralizeden_US
dc.subjectorthogonal subspace projectionen_US
dc.subjecthyperspectral imageen_US
dc.subjectmultispectralen_US
dc.subjectimageen_US
dc.subjectsubpixel detectionen_US
dc.subjectsubspace projection approachen_US
dc.subjectclassificationen_US
dc.titleGeneralized constrained energy minimization approach to subpixel target detection for multispectral imageryen_US
dc.typeJournal Articlezh_TW
dc.identifier.doi10.1117/1.602486zh_TW
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeJournal Article-
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