Signal-dependent noise modelling and estimation of new-generation imaging spectrometers - Alparone, L.; Selva, M.; Aiazzi, B.; Baronti, S.; Butera, F.; Chiarantini, L. (2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009)
This paper deals with an original method suitable for estimating the noise introduced by optical imaging systems, such as CCD cameras, multispectral scanners and imaging spectrometers. 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 signal-independent components of the noise power, respectively. Experimental results carried out on a simulated noisy image and on true data from a modern generation airborne imaging spectrometer highlight the accuracy of the proposed method and its robustness to textures that may lead to a gross over-estimation of the noise, for high SNR.