Abstract
This paper proposes an unsupervised algorithm for airport runway area detection based on super-pixel PolSAR image classification. First, the simple linear iterative clustering (SLIC) algorithm are used to obtain super-pixel image by segmenting the PauliRGB image in order to reduce computational complexity and save computing time. Then, VAT-DBE algorithm is used to estimate and obtain the number of clusters of the image automatically. Combing the polarization information, the super-pixel image is classified by the method of spectral clustering. After that, the suspected airport runway area is extracted according to the scattering characteristics of the runway and classification result. Finally, the airport runway area is detected by using structural and topological characteristics of the runways. The experimental results show that the proposed algorithm can detect the airport runway area effectively with a clear outline, complete structure, and low false alarm rate. It also needs less time and a priori information compared with other methods.
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Acknowledgements
The authors also would like to thank the support of the National Natural Science Foundation of China (No.61571442, No. 61471365), the National Key Research and Development Program of China (No.2016YFB0502405), and National University’s Basic Research Foundation of China (No. 3122014C004).
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Han, P., Lin, Z., Lu, X., Shi, Q., Zhang, Z. (2019). Automatic Detection of Airport Runway Area Based on Super-Pixel PolSAR Image Classification. In: Electronic Navigation Research Institute (eds) Air Traffic Management and Systems III. EIWAC 2017. Lecture Notes in Electrical Engineering, vol 555. Springer, Singapore. https://doi.org/10.1007/978-981-13-7086-1_14
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DOI: https://doi.org/10.1007/978-981-13-7086-1_14
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