caa a22 4500 606209891 CHVBK 20210128101030.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11220-015-0113-4 doi (NATIONALLICENCE)springer-10.1007/s11220-015-0113-4 Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging [Elektronische Daten] [Hai-Wen Chen, Mike McGurr, Mark Brickhouse] We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor. Springer Science+Business Media New York, 2015 Hyper-spectral imagery (HSI) nationallicence Double-threshold scheme nationallicence Feature transformation (FT) detection method nationallicence Automated best spectral band and fused band-pair selection process nationallicence ROC curve estimation nationallicence Chen Hai-Wen Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut McGurr Mike Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut Brickhouse Mark Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-33 1557-2064 16:1<1 2015 16 11220 https://doi.org/10.1007/s11220-015-0113-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11220-015-0113-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen Hai-Wen Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut NATIONALLICENCE 700 1- McGurr Mike Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut NATIONALLICENCE 700 1- Brickhouse Mark Booz Allen Hamilton Inc., 3rd Floor, 4694 Millennium Drive, 21017, Belcamp, MD, USA aut NATIONALLICENCE 773 0- Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-33 1557-2064 16:1<1 2015 16 11220