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Unsupervised classification and analysis of natural scenes from polarimetric interferometric SAR data

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3 Author(s)
Ferro-Famil, L. ; A. R. T. Lab., Univ. of Rennes, France ; Pottier, E. ; Lee, J.S.

In this paper is introduced a classification approach for polarimetric interferometric SAR data sets, based on the analysis of an interferometric (6×6) polarimetric coherency matrix properties. From the Wishart probability density function of this polarimetric representation, is defined a maximum likelihood decision rule to perform an iterative adaptive classification. Another classification scheme based on the derivation of the conditional probability of the cross-correlation between both data sets is presented

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Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International  (Volume:6 )

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