Abstract

In this letter, an edge detector using weighted directional Bhattacharyya coefficients (WDBCs) is proposed to improve the edge detection performance on real synthetic aperture radar (SAR) images. The Bhattacharyya coefficient (BC) is a similarity measure that considers the grayscale distribution of pixels around edges and gives a better description of textured and nonuniform regions than the ratio of averages (ROAs). However, in addition to the grayscale distribution, the spatial distribution of pixels around the edges also has a significant impact on the edge strength. To consider both grayscale and spatial distribution, the weighted histograms are computed by Gaussian-Gamma-shaped (GGS) bi-windows to obtain WDBCs in eight directions. Then the edge strength map (ESM) and edge direction map (EDM) are defined by WDBCs. The edge detector can be obtained after non-maximum suppression and hysteresis thresholding. Experimental results on real SAR images compared with five existing detectors show the effectiveness of the proposed detector.

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