A Fast Hyperspectral Anomaly Detection Algorithm Based on Greedy Bilateral Smoothing and Extended Multi-Attribute Profile

To address the difficulty of separating background materials from similar materials associated with the use of “single-spectral information” for hyperspectral anomaly detection, a fast hyperspectral anomaly detection algorithm based on what we term the “greedy bilateral smoothing and extended multi-...

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書誌詳細

出版年:	Remote Sensing
主要な著者:	Senhao Liu, Lifu Zhang, Yi Cen, Likun Chen, Yibo Wang
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2021-10-01
主題:	hyperspectral imagery (HSI) anomaly detection low-rank and sparse matrix decomposition extended multi-attribute profiles
オンライン･アクセス:	https://www.mdpi.com/2072-4292/13/19/3954