Regression techniques for material identification in hyperspectral data

Identification of materials in hyperspectral imagery is a fundamental analysis task. Materials are often identified by building pixel models using a library of reference spectra along with a regression technique. This paper describes several regression techniques that are useful in modeling hyperspectral pixels, demonstrates the characteristics of the algorithms on simulated data, and compares the strengths and weaknesses of the techniques