SAR interferogram MAP filtering based on stationary wavelet transform

Strong speckle noise of SAR interferogram is a great obstacle to phase unwrapping. In this article, we propose to filter this noise with a multiresolution analysis of the interferogram, the real part and the imaginary part of the interferogram are processed respectively. Several different probability density functions are modeled with the Pearson system of distributions, then the wavelet coefficients of the noiseless data are estimated with a Bayesian model, maximizing the a posteriori probability density function. The result is compared to that of another method and shows that the proposed method is powerful to interferogram speckle noise reduction.