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Hyperspectral Target Detection Based on Spectral Weighting

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Book cover 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

Target detection has become an important research direction in hyperspectral imagery (HSI) processing. In this paper, aiming at the phenomenon that different bands have different abilities to distinguish materials, a spectral weighting detection algorithm is proposed. Firstly, relative distance between different categories as the spectral separability criterion is used to estimate the distinction ability of each band. And then different bands are endowed with different weighting coefficients. Finally, the RX and LPD algorithms are used to test the efficiency of the proposed spectral weighting method. The experimental results show that the detection algorithms based on spectral weighting have better performances than the traditional RX and LPD algorithms.

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References

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Acknowledgements

This work is supported by the National Nature Science Foundation of China (61801075), the Fundamental Research Funds for the Central Universities (3132019218).

Author information

Authors and Affiliations

  1. Information and Technology College, Dalian Maritime University, Dalian, 116026, China

    Di Wu, Yulei Wang, Yao Shi, Qingyu Zhu & Anliang Liu

  2. State Key Laboratory of Integrated Services Networks, Xidian University, Xian, China

    Yulei Wang

Authors
  1. Di Wu
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  2. Yulei Wang
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  3. Yao Shi
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  4. Qingyu Zhu
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  5. Anliang Liu
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Corresponding author

Correspondence to Di Wu .

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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© 2020 Springer Nature Singapore Pte Ltd.

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Wu, D., Wang, Y., Shi, Y., Zhu, Q., Liu, A. (2020). Hyperspectral Target Detection Based on Spectral Weighting. 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_312

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  • DOI: https://doi.org/10.1007/978-981-13-9409-6_312

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

  • eBook Packages: EngineeringEngineering (R0)

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