SAR Image despeckling using grey system theory

Abstract

Speckle noise appears in Synthetic Aperture Radar (SAR) images owing to the SAR imaging mechanism. This paper investigates and proposes a novel method on SAR images despeckling via grey system theory. In the method, we dynamically select one referential sequence to stand for inner region pixels, and a group of comparative sequences to represent the pixels to be enhanced. Then, edge pixels are distinguished from non-edge pixels via the grey relational degrees between the two kinds of sequences, and kept unchanged; while the noise and inner region pixels, taken as non-edge pixels, are adjusted to some new values. Experimental results show that the method, when being applied to both simulated and real SAR images, has a good performance in Peak Signal-to-Noise Ratio (PSNR) improvement, and outperforms most of the conventional filters: mean filter, median filter, Lee filter, Kuan filter and Frost filter.