Hyperspectral remote sensing image feature classification algorithm based on attention U2net

Miao Zhang; Lixuan Xiao; Zeyu Zhao; Yihao Wang; Xiangpeng Feng; Ning Zhang; Zhongyue Zhang; Shi Qiu

doi:10.1117/12.3017881

15 December 2023 Hyperspectral remote sensing image feature classification algorithm based on attention U2net

Miao Zhang, Lixuan Xiao, Zeyu Zhao, Yihao Wang, Xiangpeng Feng, Ning Zhang, Zhongyue Zhang, Shi Qiu

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710U (2023) https://doi.org/10.1117/12.3017881
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

Because of the problem that the large amount of remote sensing data and the difficulty of feature selection lead to inaccurate land classification, we proposed a land classification algorithm based on attention u2net using hyperspectral technology. To solve the problem of a large amount of hyperspectral image data and high dimensionality, we adopted the LDA method for dimensionality reduction. To solve the problem that the traditional deep learning network does not focus enough on key areas, an attention u2net algorithm model is proposed, which uses an attention mechanism to strengthen the network’s learning on key areas to obtain better classification accuracy. We conducted experiments based on the existing three mainstream databases, and the results showed that the algorithm achieved an accuracy of 86.6% on the Indian Pines dataset, 95.2% on the Urban dataset, and 82.7% on the Fanglu dataset. Compared with other deep learning algorithms, the average improvement was 2.5%.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Miao Zhang, Lixuan Xiao, Zeyu Zhao, Yihao Wang, Xiangpeng Feng, Ning Zhang, Zhongyue Zhang, and Shi Qiu "Hyperspectral remote sensing image feature classification algorithm based on attention U2net", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710U (15 December 2023); https://doi.org/10.1117/12.3017881

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