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    • A background memory model for hyperspectral anomaly detection

    • In the field of hyperspectral anomaly detection, researchers have proposed a background memory model, which effectively improves detection accuracy and provides new ideas for hyperspectral image processing.
    • Vol. 28, Issue 3, Pages: 717-729(2024)   

      Received:29 April 2021

      Published:07 March 2024

    • DOI: 10.11834/jrs.20221241     

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  • Xie W Y,Zhong J P and Li Y S. 2024. A background memory model for hyperspectral anomaly detection. National Remote Sensing Bulletin, 28(3):717-729 DOI: 10.11834/jrs.20221241.
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相关作者

Weiying XIE 西安电子科技大学综合业务网理论及关键技术国家重点实验室
Jiaping ZHONG 西安电子科技大学综合业务网理论及关键技术国家重点实验室
Yunsong LI 西安电子科技大学综合业务网理论及关键技术国家重点实验室
XIE Donghui 北京师范大学 地理科学学部 遥感科学国家重点实验室
LI Yi 北京师范大学 地理科学学部 遥感科学国家重点实验室
ZHOU Kun 北京师范大学 地理科学学部 遥感科学国家重点实验室
ZHANG Zhixiang 北京师范大学 地理科学学部 遥感科学国家重点实验室
JIN Lin 北京师范大学 地理科学学部 遥感科学国家重点实验室

相关机构

State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University
Aerospace Information Research Institute, Chinese Academy of Sciences
Faculty of Geosciences and Engineering, Southwest Jiaotong University
Chengdu Institute of Plateau Meteorology, China Meteorological Administration
School of Environmental and Geographical Sciences, Shanghai Normal University
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