Median-spectral-spatial transformation of hyperspectral data for sub-pixel anomaly detection

Amber D. Fischer

doi:10.1117/12.778072

11 April 2008 Median-spectral-spatial transformation of hyperspectral data for sub-pixel anomaly detection

Amber D. Fischer

Proceedings Volume 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV; 69660R (2008) https://doi.org/10.1117/12.778072
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

Citation Download Citation

Amber D. Fischer "Median-spectral-spatial transformation of hyperspectral data for sub-pixel anomaly detection", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660R (11 April 2008); https://doi.org/10.1117/12.778072

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