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Proceedings Paper

Median-spectral-spatial transformation of hyperspectral data for sub-pixel anomaly detection
Author(s): Amber D. Fischer
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Paper Abstract

This paper extends the field of hyperspectral anomaly and target detection by introducing a new approach for preprocessing hyperspectral image data. In this study, we investigate the Median-Spectral-Spatial Transformation as an approach to draw out the sub-pixel difference characterizations of anomalous spectra. By implementing this preprocessing step, we have realized a significant improvement in false alarm reduction with increased probability of detection for sub-pixel targets. Sub-pixel anomalies contain target information consisting of only a small fraction of an image pixel's surface reflected material content. To demonstrate the efficacy of our approach, we compare results from RX anomaly detection across multiple HSI images.

Paper Details

Date Published: 11 April 2008
PDF: 11 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660R (11 April 2008); doi: 10.1117/12.778072
Show Author Affiliations
Amber D. Fischer, 21st Century Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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