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Hyperspectral Image Classification Based on 3D Calibrated Attention

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Proceedings of the 8th China High Resolution Earth Observation Conference (CHREOC 2022) (CHREOC 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 969))

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Abstract

Hyperspectral image (HSI) classification aiming at identifying the pixel-level attributes, is a challenging task in remote sensing image interpretation. Informative features play an important role in HSI classification. Existing attention-based convolutional neural networks treat each convolutional layer as a separate process that miss the correlation among different layers. To slove the problem, we introduce the 3D calibrated attention module (3DCAM) to model the holistic dependencies among channels and positions. In particular, The 3DCAM can be used for the correlation among channels to achieve more powerful feature representation and correlation learning. Furthermore, we design a 3D calibrated attention-based network, which integrates 3D-CNN and 2D-CNN layers. Both the spectral and spatial feature are employed for classification. Extensive experiments on the Indian Pines and Pavia University datasets demonstrate that the proposed method performs favorably against three closely related methods.

This work was supported in part by the National Key Research and Development Program of China under Grant 2018AAA0100602, and in part by the National Natural Science Foundation of Shandong Province under Grant ZR2019QD011.

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Authors and Affiliations

  1. School of Computer Science and Technology, Ocean University of China, Qingdao, 266100, China

    Menglin Zhang & Feng Gao

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  1. Menglin Zhang
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  2. Feng Gao
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Correspondence to Feng Gao .

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Editors and Affiliations

  1. China Aerospace Science and Technology, Beijing, China

    Liheng Wang

  2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

    Yirong Wu

  3. Wuhan University, Wuhan, China

    Jianya Gong

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Zhang, M., Gao, F. (2023). Hyperspectral Image Classification Based on 3D Calibrated Attention. In: Wang, L., Wu, Y., Gong, J. (eds) Proceedings of the 8th China High Resolution Earth Observation Conference (CHREOC 2022). CHREOC 2022. Lecture Notes in Electrical Engineering, vol 969. Springer, Singapore. https://doi.org/10.1007/978-981-19-8202-6_20

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  • DOI: https://doi.org/10.1007/978-981-19-8202-6_20

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  • Print ISBN: 978-981-19-8201-9

  • Online ISBN: 978-981-19-8202-6

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