Hyperspectral Anomaly Detection via Graph Dictionary-Based Low Rank Decomposition with Texture Feature Extraction

Hyperspectral Anomaly Detection via Graph Dictionary-Based Low Rank Decomposition with Texture Feature Extraction

The accuracy of anomaly detection in hyperspectral images (HSIs) faces great challenges due to the high dimensionality, redundancy of data, and correlation of spectral bands. In this paper, to further improve the detection accuracy, we propose a novel anomaly detection method based on texture featur...

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Bibliographic Details
Main Authors: Shangzhen Song, Yixin Yang, Huixin Zhou, Jonathan Cheung-Wai Chan
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
hyperspectral image
anomaly detection
graph theory
low rank decomposition
texture feature
Online Access:https://www.mdpi.com/2072-4292/12/23/3966

Internet

https://www.mdpi.com/2072-4292/12/23/3966

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