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Airport object extraction based on visual attention mechanism and parallel line detection
Author(s): Jing Lv; Wen Lv; Libao Zhang
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Paper Abstract

Target extraction is one of the important aspects in remote sensing image analysis and processing, which has wide applications in images compression, target tracking, target recognition and change detection. Among different targets, airport has attracted more and more attention due to its significance in military and civilian. In this paper, we propose a novel and reliable airport object extraction model combining visual attention mechanism and parallel line detection algorithm. First, a novel saliency analysis model for remote sensing images with airport region is proposed to complete statistical saliency feature analysis. The proposed model can precisely extract the most salient region and preferably suppress the background interference. Then, the prior geometric knowledge is analyzed and airport runways contained two parallel lines with similar length are detected efficiently. Finally, we use the improved Otsu threshold segmentation method to segment and extract the airport regions from the salient map of remote sensing images. The experimental results demonstrate that the proposed model outperforms existing saliency analysis models and shows good performance in the detection of the airport.

Paper Details

Date Published: 5 October 2017
PDF: 7 pages
Proc. SPIE 10432, Target and Background Signatures III, 104320S (5 October 2017); doi: 10.1117/12.2280449
Show Author Affiliations
Jing Lv, North China Electric Power Univ. (China)
Wen Lv, Beijing Normal Univ. (China)
Libao Zhang, Beijing Normal Univ. (China)


Published in SPIE Proceedings Vol. 10432:
Target and Background Signatures III
Karin U. Stein; Ric Schleijpen, Editor(s)

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