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|Title:||Unsupervised multiscale change detection in multitemporal synthetic aperture radar images|
|Source:||Celik, T. (2009). Unsupervised multiscale change detection in multitemporal synthetic aperture radar images. European Signal Processing Conference : 1547-1551. ScholarBank@NUS Repository.|
|Abstract:||In this paper, an unsupervised change detection technique for synthetic aperture radar (SAR) images is proposed by conducting probabilistic Bayesian inferencing with expectation maximization-based parameter estimation to perform unsu-pervised thresholding over the data collected from the dual-tree complex wavelet transform (DT-CWT) subbands generated at the various scales. The proposed approach exploits a DT-CWT-based multiscale decomposition of the log-ratio image aimed at achieving different scales of representation of the change signal. Experimental results obtained on multitemporal SAR images acquired by the ERS-1, and JERS satellites confirm the effectiveness of the proposed approach. © EURASIP, 2009.|
|Source Title:||European Signal Processing Conference|
|Appears in Collections:||Staff Publications|
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