Man-made target detection method based on the red-edge spectral information in natural background

Ting Li; Jindong Li; Jiarong Xiao; Xiao Liu; Haitao Tang

doi:10.1117/12.2652038

23 January 2023 Man-made target detection method based on the red-edge spectral information in natural background

Ting Li, Jindong Li, Jiarong Xiao, Xiao Liu, Haitao Tang

Proceedings Volume 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology; 125572C (2023) https://doi.org/10.1117/12.2652038
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Man-made target detection in the natural background is the core problem of high-resolution optical remote sensing image interpretation, and it is an important application direction in the target recognition, situation awareness, and other fields. This paper proposes a man-made target detection method based on red-edge spectral information in the natural background. In this method, the red-edge spectrum information of vegetation is used to suppress background interference and narrow the search area in large remote sensing images, to improve the probability of target detection. The automatic extraction model of man-made targets is trained by the public dataset COD10K and self-constructed remote sensing dataset, and detection experiments are carried out by using the multispectral images from the WorldView-3 satellite and the Sentinel-2 A/B satellites. The experimental results show that the proposed algorithm has high detection accuracy and fast detection speed for the green runway, green buildings, and another man-made targets in the forest or grassland. Compared with the traditional man-made target detection algorithm, this method is more suitable for the rapid search of large area remote sensing images.

Citation Download Citation

Ting Li, Jindong Li, Jiarong Xiao, Xiao Liu, and Haitao Tang "Man-made target detection method based on the red-edge spectral information in natural background", Proc. SPIE 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology, 125572C (23 January 2023); https://doi.org/10.1117/12.2652038

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