Abstract
Using small rotor UAV, this paper acquired the images of qionghalajun village of the artushi city in Xinjiang autonomous region. Then, two image analysis methods of object-oriented and pixel-oriented methods, respectively, were used to extract the building of the study area. It results show that the object-oriented method can effectively remove the impact of salt and pepper noise on classification and ensure the integrity of the shapes of the buildings. But the impact of different objects with similar spectral and texture information will decrease the classification accuracy. In the pixel-oriented extraction method, the improved mathematical morphology algorithm is added, which can effectively improve salt and pepper noise, maintain the continuity and integrity of the edge of the building, and solve the problem of partial farmland and houses in the object-oriented method.
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Acknowledgements
This work was jointly supported by the National Key R&D Program of China (No. 2018YFC1504403 and No. 2018YFC1504503), the National Natural Science Foundation of China (Grant No. 41601390), and the China Earthquake Administration Special Project Surplus Fund (High Resolution Rapid Post-Earthquake Assessment Techniques)
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Wu, H., Nie, G., Fan, X. (2020). Comparison of Buildings Extraction Algorithms Based on Small UAV Aerial Images. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_10
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DOI: https://doi.org/10.1007/978-3-030-60952-8_10
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