Probabilistic anomaly detector for remotely sensed hyperspectral data-Reference-Cited by-同舟云学术

Probabilistic anomaly detector for remotely sensed hyperspectral data

Published:2014-11-03 Issue:1 Volume:8 Page:083538
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:en
Short-container-title:J. Appl. Remote Sens

Author:

Gao Lianru¹,Guo Qiandong²,Plaza Antonio³,Li Jun⁴,Zhang Bing¹

Affiliation:

1. Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Science, No. 9 Dengzhuang South Road, Beijing 100094, China

2. University of South Florida, School of Geosciences, 4202 East Fowler Avenue, Tampa, Florida 33620, United States

3. University of Extremadura, Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Avda. de la Universidad S/N, Cáceres 10071, Spain

4. Sun Yat-sen University, School of Geography and Planning, No. 135 Xingang Xi Road, Guangzhou 510275, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference36 articles.

1. Hyperspectral Remote Sensing

2. Anomaly detection from hyperspectral imagery

3. Anomaly detection and classification for hyperspectral imagery

4. Constrained subpixel target detection for remotely sensed imagery

5. Mapping the distribution of mine tailings in the Coeur d'Alene River Valley, Idaho, through the use of a constrained energy minimization technique

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