On the incorporation of spatial information to endmember extraction: Survey and algorithm comparison

Abstract

Several well-known algorithms have been used for endmember extraction and spectral unmixing of hyperspectral imagery by considering only the spectral properties of the data when conducting the search. However, it might be beneficial to incorporate the spatial arrangement of the data in the development of endmember extraction and spectral unmixing algorithms. In this paper, we provide a survey on the use of spatial information in endmember extraction and further compare six different algorithms (three of which only use spectral information) in order to substantiate the impact of using spatial-spectral information versus only spectral information when searching for image endmembers. The comparison is carried out using a synthetic hyperspectral scene with spatial patterns generated using fractals, and a real hyperspectral scene collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS).