Quality Assessment of Data Products from a New Generation Airborne Imaging Spectrometer

This work focuses on the assessment of noise parameters characterizing the hyperspectral images collected by a new generation high resolution sensor manufactured by Se lex Galileo S.p.A., in Italy, and named Hyper SIM-GA, which is an imaging spectrometer operating in the push-broom configuration, with 512 bands (2 nm bandwidth) and 256 bands (6 nm bandwidth) in the V-NIR and SWIR wavelengths, respectively. To this purpose, an original method suitable for estimating the noise introduced by optical imaging systems is described. The power of the signal-dependent photonic noise is decoupled from that of the signal-independent noise generated by the electronic circuitry. The method relies on the multivariate regression of local sample mean and variance. Statistically homogeneous pixels produce scatter-points that are clustered along a straight line, whose slope and intercept measure the signal-dependent and the signal-independent components of the noise power, respectively. Experimental results on radiance data acquired by SIM-GA, highlight the accuracy of the proposed method and its robustness to image textures that may lead to a gross overestimation of the noise.