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.


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    Title :

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


    Contributors:
    Bovolo, F. (author) / Bruzzone, L. (author)


    Publication date :

    2005-01-01


    Size :

    272542 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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