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)
Nicola Acito, Nicola Acito, Salvatore Resta, Salvatore Resta, Marco Diani, Marco Diani, Giovanni Corsini, 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 . Submission:
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