Hyperspectral Anomaly Detection via Spatial Density Background Purification

Hyperspectral Anomaly Detection via Spatial Density Background Purification

In the research of anomaly detection methods, obtaining a pure background without abnormal pixels can effectively improve the detection performance and reduce the false-alarm rate. Therefore, this paper proposes a spatial density background purification (SDBP) method for hyperspectral anomaly detect...

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Bibliographic Details
Main Authors:	Bing Tu, Nanying Li, Zhuolang Liao, Xianfeng Ou, Guoyun Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2019-11-01
Series:	Remote Sensing
Subjects:	hyperspectral image anomaly detection density peak clustering collaborative representation detector
Online Access:	https://www.mdpi.com/2072-4292/11/22/2618

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