Hysupp: An Open-Source Hyperspectral Unmixing Python Package

Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot

Abstract: This paper introduces an open-source hyperspectral unmixing Python package called HySUPP. Hyperspectral unmixing can be divided into three main categories considering the prior knowledge of the endmembers; supervised, semi-supervised, and unsupervised (blind) unmixing. HySUPP includes more than 20 Python-based unmixing approaches from different categories. In the experimental section, we use a few candidates of every category and compare different unmixing approaches. In the experimental section, a challenging simulated dataset without pure pixels is used. The results confirm the advantages of deep learning-based unmixing approaches compared to conventional techniques for all categories in terms of abundance root mean square error. Additionally, blind unmixing approaches outperform supervised and semi-supervised unmixing. The package can be found at: https://github.com/BehnoodRasti/HySUPP.