A new technique for hyperspectral image analysis with applications to anomaly detection

摘要

This paper describes a new approach to hyperspectral image analysis using spectral signature mixture models. In this new approach spectral end-member extraction andspectral unmixing are co-dependent objectives. Previous method tended to serialize these tasks. Our approach shows that superior hyperspectral modeling can be obtained through a parallel objective approach.