RESUMO
Short-wave infrared (SWIR) imaging sensors are increasingly being used in surveillance and reconnaissance systems due to the reduced scatter in haze and the spectral response of materials over this wavelength range. Typically SWIR images have been provided either as full motion video from framing panchromatic systems or as spectral data cubes from line-scanning hyperspectral or multispectral systems. Here, we describe and characterize a system that bridges this divide, providing nine-band spectral images at 30 Hz. The system integrates a custom array of filters onto a commercial SWIR InGaAs array. We measure the filter placement and spectral response. We demonstrate a simple simulation technique to facilitate optimization of band selection for future sensors.
RESUMO
A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured Rrs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.
