A novel anomaly detection method incorporating target information derived from hyperspectral imagery

	A novel anomaly detection method incorporating target information derived from hyperspectral imagery
	Guo, Qiandong 1; Pu, Ruiliang 1; Gao, Lianru 1; Zhang, Bing 1
刊名	Remote Sensing Letters
	2016
卷号	7 期号:1 页码:11-20
关键词	OPTIMIZATION ALGORITHM
通讯作者	Zhang, Bing (zb@radi.ac.cn)
英文摘要	Anomaly detection is an active research topic in hyperspectral remote sensing and has been applied in many areas including environmental monitoring, urban survey, mineral mapping, and national security. Usually, it makes a detection decision without any prior target information or background information. Several anomaly detection algorithms (e.g. Reed-Xiaoli detector, blocked adaptive computationally efficient outlier nominator and random-selection-based anomaly detector) have been developed, which rely on estimating background information only from a hyperspectral image without considering target information in making a detection decision. These methods may be efficient in general but sometimes with high false alarm rate (FAR). In order to reduce FAR, this study proposes a novel method that incorporates both background and target information, derived from the hyperspectral imagery, into anomaly detection algorithms. The target information is helpful to detect anomalies as outliers. With a scene of real airborne visible infrared imaging spectrometer data, the experimental results demonstrate that the proposed method has produced better detection results and higher time efficiency compared with those using the traditional algorithms that only consider background information. © 2015 Taylor & Francis.
学科主题	Remote Sensing; Imaging Science & Photographic Technology
类目[WOS]	Remote Sensing ; Imaging Science & Photographic Technology
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:20154801625860
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39464]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1. School of Geosciences, University of South Florida, Tampa 2.FL, United States 3. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Guo, Qiandong,Pu, Ruiliang,Gao, Lianru,et al. A novel anomaly detection method incorporating target information derived from hyperspectral imagery[J]. Remote Sensing Letters,2016,7(1):11-20.
APA	Guo, Qiandong,Pu, Ruiliang,Gao, Lianru,&Zhang, Bing.(2016).A novel anomaly detection method incorporating target information derived from hyperspectral imagery.Remote Sensing Letters,7(1),11-20.
MLA	Guo, Qiandong,et al."A novel anomaly detection method incorporating target information derived from hyperspectral imagery".Remote Sensing Letters 7.1(2016):11-20.