Recursive Local Summation of RX Detection for Hyperspectral Image Using Sliding Windows
Institute of Computer Application Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Author to whom correspondence should be addressed.
Received: 29 November 2017 / Revised: 6 January 2018 / Accepted: 9 January 2018 / Published: 13 January 2018
Anomaly detection has received considerable interest for hyperspectral data exploitation due to its high spectral resolution. Fast processing and good detection performance are practically significant in real world problems. Aiming at these requirements, this paper develops a recursive local summation RX anomaly detection approach by virtue of sliding windows. This paper develops a recursive local summation RX anomaly detection approach by virtue of sliding windows. A causal sample covariance/correlation matrix is derived for local window background. As for the real-time sliding windows, the
identity is used in recursive update equations, which could avoid the calculation of historical information and thus speed up the processing. Furthermore, a background suppression algorithm is also proposed in this paper, which removes the current under test pixel from the recursively update processing. Experiments are implemented on a real hyperspectral image. The experiment results demonstrate that the proposed anomaly detector outperforms the traditional real-time local background detector and has a significant speed-up effect on calculation time compared with the traditional detectors.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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MDPI and ACS Style
Zhao, L.; Lin, W.; Wang, Y.; Li, X. Recursive Local Summation of RX Detection for Hyperspectral Image Using Sliding Windows. Remote Sens. 2018, 10, 103.
Zhao L, Lin W, Wang Y, Li X. Recursive Local Summation of RX Detection for Hyperspectral Image Using Sliding Windows. Remote Sensing. 2018; 10(1):103.
Zhao, Liaoying; Lin, Weijun; Wang, Yulei; Li, Xiaorun. 2018. "Recursive Local Summation of RX Detection for Hyperspectral Image Using Sliding Windows." Remote Sens. 10, no. 1: 103.
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