Modelling SAR images with a generalisation of the Rayleigh distribution

Speckle noise, which is caused by the coherent addition of out-of-phase reflections, is one of the main performance limiting factors in synthetic aperture radar (SAR) imagery. Efficient statistical modeling of SAR images is a prerequisite for developing successful speckle cancellation techniques. Traditionally, due to the central limit theorem, it has been assumed that the amplitude image is distributed with a Rayleigh law. However, some experimental data does not follow the Rayleigh law. The alternative empirical models that have been suggested in the literature are either generally empirical and do not have strong theoretical justification or are computationally expensive. We develop a generalised version of the Rayleigh distribution based on the assumption that the real and imaginary parts of the received signal follow an isotropic /spl alpha/-stable law. We also present estimation methods based on negative order statistics for model fitting. Our experimental results show that the new model can describe a wide range of data (in particular urban area images) which could not be described by the classical Rayleigh model or other alternative models.