  Automatic discovery and curve fitting of absorption bands in hyperspectral
data can enable the analyst to identify materials present in a scene by
comparison with library spectra. This procedure is common in laboratory
spectra, but is challenging for sparse hyperspectral data. A procedure for
robust discovery of overlapping bands in hyperspectral data is described in
this paper. The method is capable of automatically discovering and fitting
symmetric absorption bands, can separate overlapping absorption bands in a
stable manner, and has relatively low sensitivity to noise. A comparison with
techniques already available in the literature is presented using simulated
spectra. An application is demonstrated utilizing the shortwave infrared
(2.0-2.5 micron or 5000-4000 cm-1) region. A small hyperspectral scene is
processed to demonstrate the ability of the method to detect small shifts in
absorption wavelength caused by varying white mica chemistry in a natural
setting.
