Complex Isotropic {\alpha}-Stable-Rician Model for Heterogeneous SAR Images

TL;DR

This paper proposes the Complex Isotropic -Stable-Rician (CIb5SR) model for SAR images, offering a new way to accurately characterize heterogeneous scenes with an efficient parameter estimation method.

Contribution

It introduces the CIb5SR model based on Lévy b5-stable distribution and develops a novel parameter estimation approach, improving modeling of diverse SAR image features.

Findings

CIb5SR outperforms existing models in fitting heterogeneous SAR data

The model effectively captures complex scene heterogeneity

Potential applications in SAR image classification and target detection

Abstract

This article introduces a novel probability distribution model, namely Complex Isotropic {\alpha}-Stable-Rician (CI{\alpha}SR), for characterizing the data histogram of synthetic aperture radar (SAR) images. Having its foundation situated on the L\'evy {\alpha}-stable distribution suggested by a generalized Central Limit Theorem, the model promises great potential in accurately capturing SAR image features of extreme heterogeneity. A novel parameter estimation method based on the generalization of method of moments to expectations of Bessel functions is devised to resolve the model in a relatively compact and computationally efficient manner. Experimental results based on both synthetic and empirical SAR data exhibit the CI{\alpha}SR model's superior capacity in modelling scenes of a wide range of heterogeneity when compared to other state-of-the-art models as quantified by various performance metrics. Additional experiments are conducted utilizing large-swath SAR images which encompass mixtures of several scenes to help interpret the CI{\alpha}SR model parameters, and to demonstrate the model's potential application in classification and target detection.