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Proceedings Paper

A novel parallel algorithm for airport runway segmentation in satellite images using priority directional region growing strategy based on ensemble learning
Author(s): Fei Duan; Yu-Jin Zhang
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Paper Abstract

This paper addresses the problem of airport runway segmentation in satellite images with complex background clutter. To this ends, we propose a novel ensemble learning based parallel runway segmentation algorithm. The contributions of our work can be summarized as follows: (a) we propose the concept of Priority Directional Region Growing. (b)We introduce the Bresenham's line generating algorithm into our segmentation task to better utilize the structural a priori. (c) we adopt a two-stage strategy to better segment the regions corresponding to the airport runway by applying the traditional region growing method and our priority directional (two orthogonal directions in our problem) region growing method sequentially. (d) In our runway segmentation algorithm, the ensemble-learning strategy is used to combine the growing results of each detected line segment. In addition, those thin side branches, which have significantly different width, are eliminated. To evaluate the effectiveness of our algorithm, extensive simulations are carried out on the testing images obtained from Google Map. Our experimental results show that the proposed algorithm can effectively and efficiently segmented the airport region, generate relatively neat boundaries of the runways, and have great superiority over the state-of-the-art methods.

Paper Details

Date Published: 25 January 2011
PDF: 8 pages
Proc. SPIE 7872, Parallel Processing for Imaging Applications, 78720A (25 January 2011); doi: 10.1117/12.872636
Show Author Affiliations
Fei Duan, Tsinghua Univ. (China)
Yu-Jin Zhang, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 7872:
Parallel Processing for Imaging Applications
John D. Owens; I-Jong Lin; Yu-Jin Zhang; Giordano B. Beretta, Editor(s)

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