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dc.contributor.authorZhou, Jun
dc.contributor.authorLiang, Jie
dc.contributor.authorQian, Yuntao
dc.contributor.authorGao, Yongsheng
dc.contributor.authorTong, Lei
dc.contributor.editorNaoto Yokoya, Jocelyn Chanussot
dc.date.accessioned2017-12-19T01:51:09Z
dc.date.available2017-12-19T01:51:09Z
dc.date.issued2015
dc.identifier.isbn9781467390156
dc.identifier.issn2158-6268
dc.identifier.doi10.1109/WHISPERS.2015.8075474
dc.identifier.urihttp://hdl.handle.net/10072/355891
dc.description.abstractJoint spectral-spatial information based classification is an active topic in hyperspectral remote sensing. Current classification approaches adopt a random sampling strategy to evaluate the performance of various classification systems. Due to the limitation of benchmark data, sampling of training and testing data is performed on the same image. In this paper, we point out that while training with random sampling is practical for hyperspectral image classification, it has intrinsic problems in evaluating spectral-spatial information based classifiers. This statement is supported by several experiments, and has lead to the proposal of a new sampling strategy for comparing spectral spatial information based classifiers.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencename7th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS)
dc.relation.ispartofconferencetitle2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS)
dc.relation.ispartofdatefrom2015-06-02
dc.relation.ispartofdateto2015-06-05
dc.relation.ispartoflocationTokyo, JAPAN
dc.relation.ispartofpagefrom4 pages
dc.relation.ispartofpageto4 pages
dc.relation.ispartofvolume2015-June
dc.subject.fieldofresearchImage Processing
dc.subject.fieldofresearchcode080106
dc.titleOn the sampling strategies for evaluation of joint spectral-spatial information based classifiers
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2015 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.
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorZhou, Jun
gro.griffith.authorTong, Lei


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