Spectroscopy and Spectral Analysis, Volume. 42, Issue 4, 1285(2022)

Adaptability Analysis of Multiple Features Detection Algorithms Based on Fusion Degree Model Between Target and Environment

Xian-ming DENG1,1;... Tian-cai ZHANG1,*, Zeng-can LIU1,1;, Zhong-sheng LI1,1;, Jie XIONG1,1;, Yi-xiang ZHANG1,1;, Peng-hao LIU1,1;, Yi CEN2,2; *; and Fa-lin WU1,1; |Show fewer author(s)
Author Affiliations
  • 11. The 59th Research Institute of China Ordnance Industry, Chongqing 400039, China
  • 22. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
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    References(6)

    [2] N Wang, Y Zhai, L Zhang et al. IEEE Geoscience Remote Sensing Letter, 13, 1059(2016).

    [7] J Ingram, E Lo. Hyperspectral Anomaly Detection Based on Minimum Generalized Variance Method. Proc SPIE, 6966, 696603(2008).

    [9] C I Chang, M Hsueh, H Ren et al. Proc SPIE, 5159, 339(2004).

    [12] C I Chang. Hyperspectral Data Processing: Algorithm Design and Analysis. John Wiley & Sons(2013).

    [14] J A Herweg, J P Kerekes, O Weatherbee et al. Proc SPIE, 8390, 839028(2012).

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    Xian-ming DENG, Tian-cai ZHANG, Zeng-can LIU, Zhong-sheng LI, Jie XIONG, Yi-xiang ZHANG, Peng-hao LIU, Yi CEN, Fa-lin WU. Adaptability Analysis of Multiple Features Detection Algorithms Based on Fusion Degree Model Between Target and Environment[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1285

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    Paper Information

    Category: Research Articles

    Received: Dec. 11, 2020

    Accepted: --

    Published Online: Jul. 25, 2023

    The Author Email: ZHANG Tian-cai (cenyi@radi.ac.cn)

    DOI:10.3964/j.issn.1000-0593(2022)04-1285-08

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