Speckle removal and change preservation by distance-driven anisotropic diffusion of synthetic aperture radar temporal stacks

Abstract

We propose a method that smoothes spatially and uses, but also preserves, temporal information of synthetic aperture radar image stacks. To provide smoothing of such imagery without effacing temporal changes in the scene, we put forth an anisotropic diffusion technique, using a PDE approach. This approach smoothes uniform areas and preserves and enhances edges, such as roads or other features. In order to use this anisotropic diffusion technique, a homogeneous region must first be selected in the image to calculate statistics of the speckle noise. We propose a method that uses the temporal information to automatically select a homogeneous region prior to smoothing. Our proposed smoothing method calculates the distance between either pixel time-series or pixel CDFs as a measure of similarity, or uniformity. Results demonstrate the efficacy of the approach on real and synthetic data, showing lower mean squared ratio and higher structural similarity index than leading methods, as well as temporal change preservation.