Coarse-to-fine wavelet-based airport detection

Cheng Li; Shuigen Wang; Zhaofeng Pang; Baojun Zhao

doi:10.1117/12.2199619

8 October 2015 Coarse-to-fine wavelet-based airport detection

Cheng Li, Shuigen Wang, Zhaofeng Pang, Baojun Zhao

Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96751S (2015) https://doi.org/10.1117/12.2199619
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

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.

Citation Download Citation

Cheng Li, Shuigen Wang, Zhaofeng Pang, and Baojun Zhao "Coarse-to-fine wavelet-based airport detection", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751S (8 October 2015); https://doi.org/10.1117/12.2199619

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available