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Hyperspectral Image Classification Based on Bidirectional Gated Recurrent Units

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Communications, Signal Processing, and Systems (CSPS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 571))

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Abstract

The hyperspectral image classification method based on recurrent neural network (RNN) regards the spectral values of all bands of each pixel as spectral sequences. But a one-way RNN can only focus on current input and past memory states, not future memories. And RNN itself has the problem of severe gradient vanish. In this paper, bidirectional gated recurrent units (BiGRU) is used for the classification of hyperspectral images. Bi-directional can not only integrate past memory state and future memory state, but also solve the gradient punishment problem of RNN to a certain extent. And the proposed method obtains better classification performance.

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References

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Acknowledgements

This work was supported by the National Key R&D Program of China (2016YFB0502502) and the National Natural Science Foundations of China (61871150).

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Authors and Affiliations

  1. School of Electronic Engineering, Heilongjiang University, Harbin, 150080, China

    Yong Liu, Hongchang He, Xiaofei Wang, Yu Wang & Runxing Chen

Authors
  1. Yong Liu
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  2. Hongchang He
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  3. Xiaofei Wang
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  4. Yu Wang
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  5. Runxing Chen
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Corresponding author

Correspondence to Xiaofei Wang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China

    Zhenyu Na

  5. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

    Min Jia

  6. College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Liu, Y., He, H., Wang, X., Wang, Y., Chen, R. (2020). Hyperspectral Image Classification Based on Bidirectional Gated Recurrent Units. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_180

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  • DOI: https://doi.org/10.1007/978-981-13-9409-6_180

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

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