  Endmember variability is an important factor for accurately unveiling vital
information relating the pure materials and their distribution in hyperspectral
images. Recently, the extended linear mixing model (ELMM) has been proposed as
a modification of the linear mixing model (LMM) to consider endmember
variability effects resulting mainly from illumination changes. In this paper,
we further generalize the ELMM leading to a new model (GLMM) to account for
more complex spectral distortions where different wavelength intervals can be
affected unevenly. We also extend the existing methodology to jointly estimate
the variability and the abundances for the GLMM. Simulations with real and
synthetic data show that the unmixing process can benefit from the extra
flexibility introduced by the GLMM.
