Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models

Lionel Bombrun (1, 2) , Gabriel Vasile (1) , Michel Gay (3, 1) , Felix Totir (1)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
2 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)
3 GIPSA-Services - GIPSA-Services

In this paper, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter. Then, a detailed analysis is carried out to evaluate the potential of this new multivariate distribution. It is implemented in a hierarchical maximum likelihood segmentation algorithm. The segmentation results are shown on both synthetic and high-resolution PolSAR data at the X- and L-bands. Finally, some methods are examined to determine automatically the "optimal" number of segments in the final partition.

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

Lionel Bombrun, Gabriel Vasile, Michel Gay, Felix Totir. Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49 (2), pp.726-737. ⟨10.1109/TGRS.2010.2060730⟩. ⟨hal-00561129⟩