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28 October 2006Extraction of linear features on SAR imagery
Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge
detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of
extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the
computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a
great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear
features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough
Transform. The presented improved method makes full use of the directional information of each edge candidate points
so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main
linear features on SAR imagery have been extracted automatically. The method saves storage space and computational
time, which shows its effectiveness and applicability.
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Junyi Liu, Deren Li, Xin Mei, "Extraction of linear features on SAR imagery," Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64190Z (28 October 2006); https://doi.org/10.1117/12.713006