Abstract
In this paper, we apply higher ordered statistics filters to hyperspectral data to enable the detection of anomalous targets whose signatures are known. Each frame has subtracted from it an estimate based on an ordered statistics filter; the resulting frames are then combined optimally based on the covariance data of the cube and the spectral signature of the target. We show that the effect of the ordered statistic filter is to eliminate false alarms at edge points.
| Original language | English |
|---|---|
| Pages (from-to) | 35-40 |
| Number of pages | 6 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 5204 |
| State | Published - 23 Apr 2004 |
| Event | Signal and Data Processing of Small Targets 2003 - San Diego, CA, United States Duration: 5 Aug 2003 → 7 Aug 2003 |
Keywords
- Hyperspectral imagery
- Point target detection
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering