A SAR Speckle Filtering algorithm towards edge sharpening
Yunhan Dong, A.K. Milne, Bruce C. Forster · UNSWorks (University of New South Wales, Sydney, Australia) · 2024
One of the major difficulties when classifying synthetic aperture radar (SAR) images is the existence of speckle due to coherent processing. Existing speckle filtering algorithms can effectively reduce the speckle effect but unfortunately also smear edges and blur images. It is realized that fluctuations in an image can be due to either local oscillations or edge crossings. An appropriate filtering algorithm should react differently to these two types of fluctuations: To smooth local oscillations to reduce the speckle level and to enhance edge crossings to avoid blurring. Such a goal is achieved via two steps. First edge crossings are detected using the second order derivative of the Gaussian function with a proper dilation factor as the wavelet transform function; and then the traditional mean filtering algorithm using a moving window is applied only within the region in which no edge crossings exist. As a result uniform areas are smoothed and edges are effectively sharpened and enhanced. The algorithm can be used in conjunction with other popular SAR speckle filters in order to sharpen smeared edges.