Convex Set Approaches for Material Quantification in Hyperspectral Imagery

Emerging as the combination of optics and spectroscopy, the development of high resolution imaging spectrometers has allowed a new perspective for the monitoring, identification and quantification of natural resources in Earth’s surface, that is known today as hyperspectral remote sensing. An imaging spectrometer is an instrument that images the energy reflected or scattered by an object in hundred of spectral bands at different portions of the electromagnetic spectrum. Although these devices have been developed for remote sensing purposes, their applications have substantially increased in the last years because of their capabilities in materials identification, being also used in biology, medicine and related areas (Huebshman et al, 2005). In contrast to multispectral devices where each imaged spectral band covers a wide spectral range, a hyperspectral sensor has a higher spectral resolution that usually is less than 10 nm; thus, the number of spectral bands captured by the sensors represents an important difference between both technologies. Once the hyperspectral data have been appropriately calibrated taking into account the illumination factors and the atmospheric effects, the spectral information registered at each pixel of the image allows a direct identification of any imaged object based on its spectrum.