Linear and nonlinear unmixing in hyperspectral imaging

It is shown that, capitalizing on several decades of methodological developments in the geoscience and remote sensing community, most of the unmixing algorithms proposed to unmix remotely sensed images can be directly applied in the chemometrics field to process hyperspectral data arising from various scanning microscopic techniques.