Multi-Prior Twin Least-Square Network for Anomaly Detection of Hyperspectral Imagery

Multi-Prior Twin Least-Square Network for Anomaly Detection of Hyperspectral Imagery

Anomaly detection of hyperspectral imagery (HSI) identifies the very few samples that do not conform to an intricate background without priors. Despite the extensive success of hyperspectral interpretation techniques based on generative adversarial networks (GANs), applying trained GAN models to hyp...

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Bibliographic Details
Main Authors: Jiaping Zhong, Yunsong Li, Weiying Xie, Jie Lei, Xiuping Jia
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
anomaly detection
hyperspectral imagery
adversarial learning
multi-scale covariance map
least-square
unsupervised learning
Online Access:https://www.mdpi.com/2072-4292/14/12/2859

Internet

https://www.mdpi.com/2072-4292/14/12/2859

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