A novel adaptive multiscale approach to unsupervised change detection in multitemporal synthetic aperture radar (SAR) images is proposed. This approach is based on a multiresolution decomposition of the log-ratio image (obtained by a comparison of a pair of co-registered images acquired at different times on the same area) in a set of scale-dependent images characterized by a different trade-off between speckle reduction and preservation of geometrical details. For each pixel to be analyzed, a sub-set of reliable scales is identified according to an automatic local analysis of the statistic of the data. The final change-detection map is obtained according to an adaptive scale-driven fusion algorithm, which properly exploits the results of the analysis at different scales for producing an accurate and reliable change-detection map in both homogeneous and border areas. Experimental results confirm the effectiveness of the proposed technique.
An adaptive multiscale approach to unsupervised change detection in multitemporal SAR images
01.01.2005
272542 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
An Adaptive Multiscale Approach to Unsupervised Change Detection in Multitemporal SAR Images
British Library Conference Proceedings | 2005
|Unsupervised Multiscale Image Segmentation
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