Airport extraction from satellite images

In accurate remote sensing, automatic airport extraction through satellite images can be the best approach to prepare, edit, and update an efficient database. Therefore, in this article, a method for automatic airport extraction from satellite images is proposed. In the proposed method, the pre-processing of the input images was done first. For this purpose, a two-way filter has been used to reduce noise. This filter is more efficient than traditional Haas noise reduction methods such as Gaussian and preserves edges well. Also, in order to make the histogram uniform, histogram adjustment has been used.In addition, the Atsu method has been used to complete this method. Then, the holes of the extraction mask are filled and the extra parts are removed using the morphology closure operator with the appropriate element. Finally, a mask was obtained that showed the area of ​​the airport well. In order to check the proposed method in more detail, various categories were used in this field. For this purpose, various features were extracted from the image and given to 7 different classifications and the performance of each one was checked. The best performance was the KNN classification with 45.95% accuracy.

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Recommended citation: Ebadi.S.M., PoorMohamad.A. ,Malihi.L. . (2017). “Airport extraction from satellite images.” International conference on fundamental research in electrical engineering. 1(1).