SAR image edge detection via directional Bhattacharyya coefficient with its application on image segmentation
Shu‐Chen Fan, Yuhe Sun, Peng‐Lang Shui, Zejun Zhang · 2019
In this paper, a novel edge detector for synthetic aperture radar (SAR) images is proposed by introducing the Bhattacharyya coefficient (BC) combining with the rotated biwindow configuration. Based on the quantified input image, the BC is computed from two sample distribution histograms of local regions supported by the subwindows on the opposite sides of the pixel to be detected. With biwindows of different directions sliding through the image, multiple directional Bhattacharyya coefficient matrices are obtained, which are utilized to extract the edge strength map (ESM), characterizing the intensity variation in SAR images. Sequent nonmaximum suppression and hysteresis thresholding refine the extracted ESM into thin edges. Experiment results show that the proposed edge detector can accurately extract edges. Moreover, the BC-based ESM can act as a good precursor to guide SAR image segmentation based on region merging.