Filtering SAR imagery for edge detection using support value transform

Detecting Edge in synthetic aperture radar (SAR) imagery is to extract contours across the investigated SAR image. Classical edge detection methods provide a limited efficiency in SAR imagery for the presence of speckle noise. This paper deals with a novel filtering method for edge detection in SAR imagery based on support value transform (SVT). By using SVT, we decompose a SAR image into a low-frequency component image and a series of support value images (SVIs). The low-frequency image contains the slowly variation information, or the contour information in the SAR image. Then, the classical edge detection methods can be used to extract the contours of the low-frequency image. Experimental results show that this novel edge detection scheme is promising.