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dc.contributor.authorLiang, Jie
dc.contributor.authorZhou, Jun
dc.contributor.authorGao, Yongsheng
dc.contributor.editorPatrick Le Callet, Baoxin Li
dc.date.accessioned2017-05-29T12:32:46Z
dc.date.available2017-05-29T12:32:46Z
dc.date.issued2016
dc.identifier.isbn9781467399616
dc.identifier.issn1522-4880
dc.identifier.doi10.1109/ICIP.2016.7532748
dc.identifier.urihttp://hdl.handle.net/10072/124191
dc.description.abstractThis paper proposes a novel multi-dimensional morphology descriptor, tensor morphology profile (TMP), for hyperspectral image classification. TMP is a general framework to extract the multi-dimensional structures in high-dimensional data. The nth-order morphology profile is proposed to work with the nth-order tensor, which can capture the inner high order structures. This is different with the traditional mathematical morphology operations which are usually limited to two-dimensional data. By treating hyperspectral images a tensor, it is possible to extend the morphology to high dimensional data so that the powerful morphological tools can be used to analyze the hyperspectral images with spectral-spatial information fused. Experimental results on two commonly used hyperspectral images show that the tensor morphological profile consistently performs better than the extended morphological profile for hyperspectral image classification.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencename23rd IEEE International Conference on Image Processing (ICIP)
dc.relation.ispartofconferencetitle2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
dc.relation.ispartofdatefrom2016-09-25
dc.relation.ispartofdateto2016-09-28
dc.relation.ispartoflocationPhoenix, AZ
dc.relation.ispartofpagefrom2197
dc.relation.ispartofpagefrom5 pages
dc.relation.ispartofpageto2201
dc.relation.ispartofpageto5 pages
dc.relation.ispartofvolume2016-August
dc.subject.fieldofresearchImage processing
dc.subject.fieldofresearchcode460306
dc.titleTensor morphological profile for hyperspectral image classification
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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gro.griffith.authorGao, Yongsheng
gro.griffith.authorZhou, Jun


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