A neural approach to unsupervised classification of very-high resolution polarimetric SAR data

Analysis of L-band polarimetric SAR data has not been extensively carried out for undulating, heterogeneous and fragmented landscapes, where classification can become quite challenging. This paper reports results of a study on the pixel-by- pixel unsupervised classification of very-high resolution polarimetric images by self-organizing neural networks.

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