Classification of polarimetric SAR images using adaptive neighbourhood structures
Two detail-preserving classification algorithms for polarimetric SAR images are proposed and their performance are evaluated on polarimetric complex SAR images. Neighbourhood structures are adaptively selected for modelling the polarimetric amplitudes and the region labels, and for achieving detailpreservation. Experimental results obtained from multi-frequency polarimetric SAR images show that the novel schemes produce significant visual improvements for detail preservation, and exhibit equivalent or higher classification performance with respect to usual classification schemes.
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