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- Title
Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection.
- Authors
Acito, Nicola; Resta, Salvatore; Diani, Marco; Corsini, Giovanni
- 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.
- Subjects
OUTLIER detection; HYPERSPECTRAL imaging systems; RANDOM noise theory; PIXELS; SIGNAL processing; ALGORITHMS
- Publication
Optical Engineering, 2013, Vol 52, Issue 3, p1
- ISSN
0091-3286
- Publication type
Article
- DOI
10.1117/1.OE.52.3.036202