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Self-organizing Neural Networks for Unsupervised Classification of Polarimetric SAR Data on Complex Landscapes

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4 Author(s)
C. Putignano ; DISP, Univ. Tor Vergata, Rome ; G. Schiavon ; D. Solimini ; B. Trisasongko

This paper refers to a study on the pixel-by-pixel unsupervised classification of a polarimetric SAR image of a Central Italy landscape. The polarimetric data have been processed by self-organizing neural networks to test their performance in classifying a complex landscape. The discrimination accuracy attained by the self-organizing map method is compared both against that of H/A/alpha-Wishart unsupervised procedure and of a supervised scheme.

Published in:

2006 IEEE International Symposium on Geoscience and Remote Sensing

Date of Conference:

July 31 2006-Aug. 4 2006