Paper
5 January 2004 Applying ordered statistics filters for point target detection in hyperspectral data
Author Affiliations +
Abstract
In this paper, we apply highly 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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ori Raviv and Stanley R. Rotman "Applying ordered statistics filters for point target detection in hyperspectral data", Proc. SPIE 5204, Signal and Data Processing of Small Targets 2003, (5 January 2004); https://doi.org/10.1117/12.503942
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Target detection

Digital filtering

Detection and tracking algorithms

Hyperspectral target detection

Statistical analysis

Earth observing sensors

Landsat

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