Spectral Variability in a Multilinear Mixing Model

We present a new method for spectral unmixing which takes both nonlinear mixing and spectral variability into account. This is accomplished by combining the multiple endmember spectral mixture analysis (MESMA) approach with the recently developed multilinear mixing model (MLM). As the traditional approach of nonlinear unmixing of all combinations is very time consuming, we investigate a second approach, where endmember model selection is linearly performed by a fast alternative for MESMA, followed by nonlinear unmixing. We show that this approach yields similar reconstruction errors (REs) as the full combinatorial approach, and hence results in a relatively fast method for nonlinear unmixing with variability.