A novel anomaly detection method incorporating target information derived from hyperspectral imagery
文献类型：期刊论文
| 作者 | Guo, Qiandong1; Pu, Ruiliang1; Gao, Lianru1; Zhang, Bing1 |
| 刊名 | Remote Sensing Letters
 |
| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：遥感与数字地球研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。