Global and Local Real-Time Anomaly Detectors for Hyperspectral Remote Sensing Imagery

Remote Sensing

Chunhui Zhao³  Yulei Wang³  Bin Qi²  Jia Wang³  Gonzalo Pajares Martinsanz¹ 

[1] College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China; E-Mail;College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China; E-Mail:;College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China; E-Mail:

关键词: hyperspectral remote sensing;    anomaly detection;    real-time;    Woodbury matrix identity;    sliding local window;   

DOI  :  10.3390/rs70403966

来源: mdpi

【 摘 要 】

Anomaly detection has received considerable interest for hyperspectral data exploitation due to its high spectral resolution. A well-known algorithm for hyperspectral anomaly detection is the RX detector. A number of variations have been studied since then, including global and local versions for different type of anomalies. Aiming at a real-time requirement for practical applications, this paper extends the concept of global and local anomaly detectors to be real-time detectors. The algorithms exploit the fact that a true real-time detector must produce its output in a causal manner and at the same time as an input comes in. Taking advantage of the Woodbury matrix identity, the global and local real-time detectors can be implemented and processed pixel-by-pixel in real time. Both synthetic and real hyperspectral imagery are conducted to demonstrate their performance.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.