Circularity of Complex Stochastic Models in POLSAR and Multi-pass InSAR Images

Gabriel Vasile (1) , Felix Totir (1)

1 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

Polarimetry and multi-pass interferometry extend the dimensionality of SAR data, so the necessity to have multivariate statistic (and non-Gaussian, because of the high resolution) distributions as models for these types of data: such are the SIRV (Spherically Invariant Random Vectors). However, as the statistic model becomes so complicated, correctly estimating its parameters gets difficult. More, although they are versatile, the SIRV models are not guaranteed to match the PolSAR / InSAR data. To evaluate the pertinence of those models with respect to the PolSAR data, through one of their most important statistic property, namely the circularity, it is the purpose of this paper.

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

Gabriel Vasile, Felix Totir. Circularity of Complex Stochastic Models in POLSAR and Multi-pass InSAR Images. IGARSS 2012 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2012, Munich, Germany. pp.3720-3723. ⟨hal-00785995⟩