Hyperspectral Unmixing Under Endmember Variability: A Variational
Inference Framework
Hyperspectral Unmixing Under Endmember Variability: A Variational
Inference Framework
This work proposes a variational inference (VI) framework for hyperspectral unmixing in the presence of endmember variability (HU-EV). An EV-accounted noisy linear mixture model (LMM) is considered, and the presence of outliers is also incorporated into the model. Following the marginalized maximum likelihood (MML) principle, a VI algorithmic structure is …