Spectral imaging is about projecting the 2D photometric image along with several separate spectral bands (multispectral), or along with many continuous spectral bands (hyperspectral). Thus, spectral images contain intensity values for several or many, up to several hundred, wavelengths for each pixel.
In outdoor scenarios, the radiation measured by the spectrometer contains the spectral signatures of the background of the field of view, the pollutant cloud, and the atmosphere. The basic characteristics of spectra measured by an infrared spectrometer may be described by a model in which the atmosphere is divided into plane-parallel homogeneous layers along the optical path. Numerous chemical compounds can be identified by their spectral fingerprints. The identification method is based on the approximation of a measured spectrum using reference spectra, which can be generated with the appropriate modeling software.
The research group is devoted to researching hyperspectral vision for enabling advanced analysis capabilities. The research combines the power of high-resolution spectroscopy and the high-resolution characteristics of digital imaging, to provide a hyper/multispectral imaging system capable of recording the spatially distributed reflectance, absorbance or transmittance from an object with high spectral fidelity. The spectra collected from a production plate during a measurement are analyzed using a radiative transfer model that considers chemical compositions, temperatures, and pressures, and which is finally fitted to a reference spectrum to determine the presence and concentrations of known properties by establishing spectral signatures for the specific materials.
