Improving Spectral-Based Endmember Finding by Exploring Spatial Context for Hyperspectral Unmixing

Hyperspectral unmixing, which intends to decompose mixed pixels into a collection of endmembers weighted by their corresponding fraction abundances, has been widely utilized for remote sensing image exploitation. Recent studies have revealed that spatial context of pixels is important complemental information for hyperspectral image processing. However, many well-known endmember finding (EF) algorithms identify spectrally pure spectra from...