Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICASSP.2010.5495301
DC FieldValue
dc.titleResolution selective change detection in satellite images
dc.contributor.authorCelik, T.
dc.contributor.authorCurtis, C.V.
dc.date.accessioned2014-10-16T08:48:30Z
dc.date.available2014-10-16T08:48:30Z
dc.date.issued2010
dc.identifier.citationCelik, T., Curtis, C.V. (2010). Resolution selective change detection in satellite images. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings : 970-973. ScholarBank@NUS Repository. https://doi.org/10.1109/ICASSP.2010.5495301
dc.identifier.isbn9781424442966
dc.identifier.issn15206149
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/95493
dc.description.abstractIn this paper, we propose a novel method for unsupervised change detection in satellite images. A feature vector for each pixel is extracted using the multiresolution representation of the difference image which is computed from the multitemporal satellite images of the same scene acquired at different time instances. A metric for automatically estimating the number of resolution levels used in multiresolution analysis is proposed. The dimensionality of each feature vector is reduced using principal component analysis (PCA). The feature vectors are then classified into "changed" and "unchanged" classes using k-means clustering with k = 2 to achieve a change detection map. Results are shown on real data and comparisons with the state-of-the-art techniques on advanced synthetic aperture radar (ASAR) images are provided. ©2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICASSP.2010.5495301
dc.sourceScopus
dc.subjectChange detection
dc.subjectMultiresolution analysis
dc.subjectMultitemporal satellite images
dc.subjectRemote sensing
dc.subjectUndecimated discrete wavelet transform
dc.typeConference Paper
dc.contributor.departmentCHEMISTRY
dc.description.doi10.1109/ICASSP.2010.5495301
dc.description.sourcetitleICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dc.description.page970-973
dc.description.codenIPROD
dc.identifier.isiut000287096001011
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