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12 March 2013 Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection
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Abstract
A novel technique for anomalous change detection (ACD) in hyperspectral images is presented. The technique embeds a strategy robust to residual misregistration errors that typically affect data collected by airborne platforms. Furthermore, the proposed technique mitigates the negative effects due to random noise, by means of a band selection technique aimed at discarding spectral channels whose useful signal content is low compared to the noise contribution. Band selection is performed on a per-pixel basis by exploiting the estimates of the noise variance accounting also for the presence of the signal-dependent noise component. Real data collected by a new generation airborne hyperspectral camera on a complex urban scenario are considered to test the proposed method. Performance evaluation shows the effectiveness of the proposed approach with respect to a previously proposed ACD algorithm based on the same similarity measure.
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2013/$25.00 © 2013 SPIE
Nicola Acito, Salvatore Resta, Marco Diani, and Giovanni Corsini "Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection," Optical Engineering 52(3), 036202 (12 March 2013). https://doi.org/10.1117/1.OE.52.3.036202
Published: 12 March 2013
JOURNAL ARTICLE
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