Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TGRS.2002.1006395
DC Field | Value | |
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dc.title | A novel multifractal estimation method and its application to remote image segmentation | |
dc.contributor.author | Du, G. | |
dc.contributor.author | Yeo, T.S. | |
dc.date.accessioned | 2014-06-16T09:33:09Z | |
dc.date.available | 2014-06-16T09:33:09Z | |
dc.date.issued | 2002-04 | |
dc.identifier.citation | Du, 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.issn | 01962892 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/54633 | |
dc.description.abstract | Based 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.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TGRS.2002.1006395 | |
dc.source | Scopus | |
dc.subject | Image segmentation | |
dc.subject | Multispectral estimation | |
dc.subject | Synthetic aperture radar | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.doi | 10.1109/TGRS.2002.1006395 | |
dc.description.sourcetitle | IEEE Transactions on Geoscience and Remote Sensing | |
dc.description.volume | 40 | |
dc.description.issue | 4 | |
dc.description.page | 980-982 | |
dc.description.coden | IGRSD | |
dc.identifier.isiut | 000176008900023 | |
Appears in Collections: | Staff Publications |
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