UDR: An Approximate Unbiased Difference-Ratio Edge Detector for SAR Images

Edge detection is a critical component of synthetic aperture radar (SAR) image interpretation. Due to serious speckle noise, the core problems for SAR edge detection are how to keep a constant false alarm rate (CFAR) and how to achieve unbiased localization of the edges. Aiming at these problems, this article proposes a novel edge detector with a unique structure for noise-contaminated SAR images, which creatively integrates the difference operation with ratio operation (hence named as “UDR: unbiased difference-ratio” edge detector). Theoretical analysis proves that the difference operation effectively affords the UDR unbiased localization ability for both ideal and nonideal edges, and the ratio operation provides the UDR the property of CFAR under the influence of speckle noise. Experimental results on both simulated and real-world SAR images demonstrate the unbiased localization ability of the proposed UDR edge detection, insensitive to the changes of edge contrast, the width of the transition zone and the noise level. Benefited from the superior localization precision and insensitivity to noise, the average true positive detection rate of the proposed detector is improved to 95%, outperforming the compared state-of-the-art methods.