Segmentation of polarimetric SAR data based on the fisher distribution for texture modeling

Lionel Bombrun (1) , Jean-Marie Beaulieu (2)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
2 Laboratoire de robotique

The Polarimetric Synthetic Aperture Radar (PolSAR) covariance matrix is generally modeled by a complex Wishart distribution. For textured scenes, the product model is used and the texture component is often modeled by a Gamma distribution. In this paper, authors propose to use the Fisher distribution for texture modeling. From a Fisher distributed texture component, we derive the distribution of the complex covariance matrix and we propose to implement the KummerU distribution in a hierarchical segmentation and a hierarchical clustering algorithm. Segmentation and classification results are shown on synthetic images and on ESAR L-band PolSAR data over the Oberpfaffenhofen test-site.

Mots clés: Polarimetric SAR images; Fisher distribution; Texture; KummerU; Classification; Segmentation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Lionel Bombrun, Jean-Marie Beaulieu. Segmentation of polarimetric SAR data based on the fisher distribution for texture modeling. IGARSS 2008 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2008, Boston, MA, United States. pp.350-353. ⟨hal-00369374⟩