Hyperspectral Anomaly Detection Method Based on Low Rank Total Variation Regu-larization

Hyperspectral Anomaly Detection Method Based on Low Rank Total Variation Regu-larization

Hyperspectral remote sensing technology provides abundant spectral information for exploring objects and supplies a better data source for anomaly detection. However, anomaly detection is still a challenging task without any valuable prior information. Aiming at this problem, a hyperspectral anomaly...

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Bibliographic Details
Main Author: XU Chao, ZHAN Tianming
Format: Article
Language:zho
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2020-12-01
Series:Jisuanji kexue yu tansuo
Subjects:
hyperspectral data
anomaly detection
low-rank representation
regularization
Online Access:http://fcst.ceaj.org/CN/abstract/abstract2494.shtml

Internet

http://fcst.ceaj.org/CN/abstract/abstract2494.shtml

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