Strong speckle noise of SAR interferogram is a great obstacle to phase unwrapping. In order to obtain a more accurate topographic model

a noise filtering step must be performed before the unwrapping of phase. In this article

we propose to filter this noise with a multi-resolution analysis of the interferogram

the real part and the imaginary part of the interferogram are processed seperatively. Several different probability density function are modeled with the Pearson system of distributions

then the wavelet coefficients of the noiseless data are estimated with a Bayesian model

maximizing the posteriori probability density function. The result is compared to that of three other methods and shows that the proposed method is powerful to interferogram speckle noise reduction

as well as it can preserve fine details in the interferogram that are directly related to the ground topography and maintain phase values distribution.