Proceedings Article | 23 September 2003
Proc. SPIE. 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX
KEYWORDS: Target detection, Signal to noise ratio, Short wave infrared radiation, Carbon dioxide, Data modeling, Sensors, Reflectivity, Atmospheric corrections, Data centers, Absorption
Spectral registration errors occur in hyperspectral (HS) data when the reported channel center wavelengths accompanying a data cube (commonly called the wavefile) are inaccurate. Poor spectral registration can lead to errors in water vapor retrievals and in the correction of other atmospheric gases. This, in turn, leads to erroneous overall atmospheric correction of HS data, and reduced exploitation performance. We have developed a method to detect poor spectral registration using major atmospheric spectral features. The spectral features we use are the Fraunhofer "G" line at 430 nm, to O<sub>2</sub> absorption lines at 762 nm and 1268 nm, three water vapor absorption bands at 817 nm, 935 nm, and 1135 nm, and a CO<sub>2</sub> absorption line at 2055 nm. We check the alignment of the average, uncorrected background features with MODTRAN-modeled spectral radiance data. We will present our approach to spectral registration and the wavefile correction method we developed, based on the accurate channel center wavelengths determined for the various atmospheric features. We will also present results from various sensor types.
