SAR Speckle Reduction Based on Multi-Scale Wavelets and Gauss Mixture Model
Lanying Cao · Shuju caiji yu chuli · 2005
A new algorithm for suppressing speckle in synthetic aperture radar (SAR) images is presented. According to the statistical characteristics of wavelet coefficients, Gauss mixture model is used to demonstrate the statistics of those coefficients. Using Bayesian estimator is to get the actual coefficients. Biased mean of the log-transformed image will affect the algorithm result; it is corrected before multi-scale wavelet transformation. Simulation results show that the method performs better than the common threshold de-noising method. So it can remove the noise while sustaining the edge properties of natural SAR images.