Hyperspectral anomaly detection method based on linear background removal. Issue 1 (January 2021)
- Record Type:
- Journal Article
- Title:
- Hyperspectral anomaly detection method based on linear background removal. Issue 1 (January 2021)
- Main Title:
- Hyperspectral anomaly detection method based on linear background removal
- Authors:
- Du, Huiting
Fan, Yanguo
Xu, Mingming - Abstract:
- Abstract: In view of the fact that the existing hyperspectral image anomaly detection algorithms only pay attention to distinguish between target and background by using spectral differences and ignore the correlation between pixels, and that local RX algorithm is easy to detect global non-anomalies as anomalies when the background is relatively complex, a hyperspectral anomaly detection method based on linear background removal is proposed. In this method, the edge information of hyperspectral image is obtained first, then the line part of edge image is extracted by Hough transform, and finally the local anomaly detection is carried out based on the linear background removal. By comparing the ROC curve and AUC value of this algorithm with RX algorithm and local RX algorithm, it shows that the algorithm of this paper can effectively reduce the false alarm rate of detection and has a better detection effect.
- Is Part Of:
- Journal of physics. Volume 1732:Issue 1(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1732:Issue 1(2021)
- Issue Display:
- Volume 1732, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1732
- Issue:
- 1
- Issue Sort Value:
- 2021-1732-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1732/1/012044 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25481.xml