A novel adaptive multiscale approach to unsupervlsed 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. © 2005 IEEE.

An adaptive multiscale approach to unsupervised change detection in multitemporal SAR images

Bovolo, Francesca;Bruzzone, Lorenzo
2005-01-01

Abstract

A novel adaptive multiscale approach to unsupervlsed 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. © 2005 IEEE.
2005
IEEE International Conference on Image Processing: ICIP 2005
Piscatawaj, NJ
IEEE
9780780391345
Bovolo, Francesca; Bruzzone, Lorenzo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/59989
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