Filtering of SAR images using non-local PCA
Zhihuo Xu, Yunkai Deng, Robert Wang, Wei Wang, Ning Li · Remote Sensing Letters · 2015
This letter presents a novel approach for despeckling synthetic aperture radar (SAR) images. The underlying principle is first to convert multiplicative speckle noise into additive by using logarithmic transformation. The patches’ similarity is exploited by using Kolmogorov–Smirnov (KS) measurements. Then, the proposed two-stage approach filters the noisy image using a nonlocal principal component analysis (PCA) shrinkage strategy by automatically estimating the level of the additive noise in the log-transformed image via Gaussian mixture model (GMM). The proposed approach has been compared with two current state-of-the-art methods, showing the very promising and competitive results on filtering the speckle noise.