Self-Supervised Masked Graph Autoencoder for Hyperspectral Anomaly Detection

Hyperspectral image anomaly detection faces the challenge of difficulty in annotating anomalous targets. Autoencoder(AE)-based methods are widely used due to their excellent image reconstruction capability. However, traditional grid-based image representation methods struggle to capture long-range d...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 34; pp. 6714 - 6729
Main Authors:	Tu, Bing, He, Baoliang, He, Yan, Zhou, Tao, Liu, Bo, Li, Jun, Plaza, Antonio
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Anomalies Anomaly detection autoencoder Autoencoders Decoding Detectors Feature extraction Gaussian distribution graph attention network Hyperspectral imaging Image reconstruction Kernel Laplace equations re-masking strategy Regularization Representations twice loss
ISSN:	1057-7149, 1941-0042, 1941-0042
Online Access:	Get full text
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