Spatial–Spectral Joint Hyperspectral Anomaly Detection Based on a Two-Branch 3D Convolutional Autoencoder and Spatial Filtering

Spatial–Spectral Joint Hyperspectral Anomaly Detection Based on a Two-Branch 3D Convolutional Autoencoder and Spatial Filtering

Hyperspectral anomaly detection (HAD) is an important application of hyperspectral images (HSI) that can distinguish anomalies from background in an unsupervised manner. As a common unsupervised network in deep learning, autoencoders (AE) have been widely used in HAD and can highlight anomalies by r...

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Bibliographic Details
Main Authors: Shuai Lv, Siwei Zhao, Dandan Li, Boyu Pang, Xiaoying Lian, Yinnian Liu
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Remote Sensing
Subjects:
hyperspectral image
anomaly detection
3D convolutional autoencoder
spatial–spectral joint information
spatial filtering
Online Access:https://www.mdpi.com/2072-4292/15/10/2542

Internet

https://www.mdpi.com/2072-4292/15/10/2542

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