Please use this identifier to cite or link to this item: https://doi.org/10.1109/TGRS.2002.1006395
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dc.titleA novel multifractal estimation method and its application to remote image segmentation
dc.contributor.authorDu, G.
dc.contributor.authorYeo, T.S.
dc.date.accessioned2014-06-16T09:33:09Z
dc.date.available2014-06-16T09:33:09Z
dc.date.issued2002-04
dc.identifier.citationDu, G., Yeo, T.S. (2002-04). A novel multifractal estimation method and its application to remote image segmentation. IEEE Transactions on Geoscience and Remote Sensing 40 (4) : 980-982. ScholarBank@NUS Repository. https://doi.org/10.1109/TGRS.2002.1006395
dc.identifier.issn01962892
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54633
dc.description.abstractBased on the gliding-box and relative differential box-counting algorithms, a novel method that estimates accurately the multifractal exponents, a distinct characteristics of gray-scale digital images, is proposed. Four natural texture images are used to test the performance of the novel multifractal measure. Comparisons with published methods show that the proposed method can efficiently describe texture images and can provide accurate classification results.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TGRS.2002.1006395
dc.sourceScopus
dc.subjectImage segmentation
dc.subjectMultispectral estimation
dc.subjectSynthetic aperture radar
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TGRS.2002.1006395
dc.description.sourcetitleIEEE Transactions on Geoscience and Remote Sensing
dc.description.volume40
dc.description.issue4
dc.description.page980-982
dc.description.codenIGRSD
dc.identifier.isiut000176008900023
Appears in Collections:Staff Publications

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