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Proceedings Paper

Coarse-to-fine wavelet-based airport detection
Author(s): Cheng Li; Shuigen Wang; Zhaofeng Pang; Baojun Zhao
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Paper Abstract

Airport detection on optical remote sensing images has attracted great interest in the applications of military optics scout and traffic control. However, most of the popular techniques for airport detection from optical remote sensing images have three weaknesses: 1) Due to the characteristics of optical images, the detection results are often affected by imaging conditions, like weather situation and imaging distortion; and 2) optical images contain comprehensive information of targets, so that it is difficult for extracting robust features (e.g., intensity and textural information) to represent airport area; 3) the high resolution results in large data volume, which makes real-time processing limited. Most of the previous works mainly focus on solving one of those problems, and thus, the previous methods cannot achieve the balance of performance and complexity. In this paper, we propose a novel coarse-to-fine airport detection framework to solve aforementioned three issues using wavelet coefficients. The framework includes two stages: 1) an efficient wavelet-based feature extraction is adopted for multi-scale textural feature representation, and support vector machine(SVM) is exploited for classifying and coarsely deciding airport candidate region; and then 2) refined line segment detection is used to obtain runway and landing field of airport. Finally, airport recognition is achieved by applying the fine runway positioning to the candidate regions. Experimental results show that the proposed approach outperforms the existing algorithms in terms of detection accuracy and processing efficiency.

Paper Details

Date Published: 8 October 2015
PDF: 7 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751S (8 October 2015); doi: 10.1117/12.2199619
Show Author Affiliations
Cheng Li, School of Information and Electronics, Beijing Institute of Technology (China)
Shuigen Wang, School of Information and Electronics, Beijing Institute of Technology (China)
Zhaofeng Pang, School of Information and Electronics, Beijing Institute of Technology (China)
Baojun Zhao, School of Information and Electronics, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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