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SAR image edge detection via directional Bhattacharyya coefficient with its application on image segmentation
Author(s): Shuchen Fan; Penglang Shui; Zejun Zhang; Yuhe Sun
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Paper Abstract

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.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 1104107 (15 March 2019); doi: 10.1117/12.2522837
Show Author Affiliations
Shuchen Fan, Xidian Univ. (China)
Penglang Shui, Xidian Univ. (China)
Zejun Zhang, Fujian Agriculture and Forestry Univ. (China)
Yuhe Sun, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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