Impact of informative band selection on target detection performance

Hamed Gholizadeh; Mohammad Javad Valadan Zoej; Barat Mojaradi

doi:10.1117/12.898320

26 October 2011 Impact of informative band selection on target detection performance

Hamed Gholizadeh, Mohammad Javad Valadan Zoej, Barat Mojaradi

Proceedings Volume 8180, Image and Signal Processing for Remote Sensing XVII; 81801C (2011) https://doi.org/10.1117/12.898320
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

In this paper, the effect of dimensionality reduction of hyperspectral data on 10 subpixel target detectors is investigated. The genetic algorithm (GA) and wavelet feature extraction methods are used for dimensionality reduction as they maintain physically meaningful bands and physical structure of the spectra, respectively. In the former case, the wrapper method is used to improve subpixel target detectors' results in terms of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Meanwhile, in the latter case, the AUC is used as a criterion to choose the optimum level of wavelet decomposition. Experimental results obtained from a real-world hyperspectral data and a challenging synthetic dataset approved that band selection with the wrapper method is more efficient than using target detection methods without dimensionality reduction, especially in the presence of difficult targets at subpixel level.

Citation Download Citation

Hamed Gholizadeh, Mohammad Javad Valadan Zoej, and Barat Mojaradi "Impact of informative band selection on target detection performance", Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII, 81801C (26 October 2011); https://doi.org/10.1117/12.898320

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