Automatic Spectral Unmixing of Hyperspectral Data Before Radiation Correction: Application to PHI Data

Radiation correction is often required in popular spectral unmixing of hyperspectral data, followed by interactive endmember determination methods. It involves much heavy work for the huge amount of hyperspectral data. In this paper, an uncorrected image of Push-broom Hyperspectral Imager (PHI) was automatically unmixed based on the linear mixing model, using minimum noise fraction (MNF) transformation to find the inherent dimensionality of the data, convex geometry concepts to extract endmembers and least squares method to estimate the fractional abundances. The result abundance images indicated that hyperspectral data, in subsection of appropriate size, can be unmixed before radiation correction and no apriori ground information is required.