SAR Image Edge Detection Robust to Isolated Strong Scatterers Using Anisotropic Morphological Directional Ratio Test

Edge detection via anisotropic average directional ratio (AADR) for synthetic aperture radar (SAR) images produces unwanted and fragmentized edge pixels due to the speckle noise and sporadic highlight pixels from isolated strong scatterers in real scenes. In this paper, a novel robust edge detector is developed for SAR images. Anisotropic morphological directional ratio (AMDR) is proposed to describe the intensity variation in SAR images by combining rotated biwindows and the weighted median filter (WMF). Then, multiplicative spatial and directional matched filters are presented to improve edge localization and direction estimation of the AMDR. Based on the enhanced AMDR, the edge strength map (ESM) and the edge direction map (EDM) are embedded into the route of Canny detector to extract thin edges. Moreover, an edge remedy processing is given to improve the connectivity of edges near junctions. Finally, performance comparison is conducted with the existing AADR-based detectors on synthetic and real SAR images using the receiver-operating-characteristic (ROC) curves, which shows that the proposed AMDR-based detector possesses evidently more robust ability to counteract sporadic isolated highlight pixels in SAR images than the existing AADR-based detectors do. Moreover, in the case without sporadic isolated highlight pixels, its performance is also comparable with those of existing competitive AADR-based ones.