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Communication Dans Un Congrès Année : 2013

CFAR Hierarchical Clustering of Polarimetric SAR Data

Résumé

Recently, a general approach for high-resolution polarimetric SAR (POLSAR) data classification in heterogeneous clutter was presented, based on a statistical test of equality of covariance matrices. Here, we extend that approach by taking advantage of the Constant False Alarm Ratio (CFAR) property of the statistical test in order to improve the clustering process. We show that the CFAR property can be used in the hierarchical segmentation of the POLSAR data images to automatically detect the number of clusters. The proposed method will be applied on a high-resolution polarimetric data set acquired by the ONERA RAMSES system.
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Dates et versions

hal-01010367 , version 1 (19-06-2014)

Identifiants

Citer

Pierre Formont, Miguel Angel Veganzones, Joana Frontera-Pons, Frédéric Pascal, Jean-Philippe Ovarlez, et al.. CFAR Hierarchical Clustering of Polarimetric SAR Data. IGARSS 2013 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2013, Melbourne, Australia. pp.2461-2464, ⟨10.1109/IGARSS.2013.6723319⟩. ⟨hal-01010367⟩
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