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Classification de données SAR multifréquences polarimétriques

Multi frequency polarimetric sar data classification

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Abstract

Multi frequency polarimetric sar data classification requires to consider the polarimetrie information from each data set simultaneously.

Dual data sets are classified using an iterative k-mean algorithm based on a maximum likelihood decision rule evaluated from the Wishart polarimetrie density of the 6×6 coherency matrix.

An alternative technique is also proposed which introduces the polarimetrie cross-correlation information to refine the results of classification to a small number of clusters using the conditional probability of the cross-correlation matrix.

Both new multi frequency polarimetric sar data classification methods are applied to sar data acquired over the Nezer forest (nasa /jpl AirSAR database (1989)).

Résumé

La classification de données sar polarimétriques multifréquences appairées nécessite la prise en compte de façon simultanée de ľinformation polarimétrique totale de chacune des images. Les données appairées sont classées au moyen ďun algorithme itératif des k-moyens basé sur une règle de décision au maximum de vraisemblance évaluée à partir de la densité de probabilité de Wishart de la matrice de cohérence polarimétrique 6×6.

Une seconde méthode est proposée qui, à partir de ľinformation liée à ľintercorrélation polarimétrique, permet ďaffiner les résultats ďune classification avec un nombre de classes peu élevé, en créant des classes de façon itérative à partir du calcul de la densité de probabilité conditionnelle de la matrice ďintercorrélation.

Les deux nouvelles méthodes de classification de données sar polarimétriques multi-fréquence appairées sont appliquées sur des images SAR polarimétriques de la forêt de Nezer (nasa /jpl AirSAR database (1989)).

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Ferro-Famil, L., Pottier, E. Classification de données SAR multifréquences polarimétriques. Ann. Télécommun. 56, 510–522 (2001). https://doi.org/10.1007/BF03008829

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