Spectral-textural endmember extraction

Several available techniques for endmember extraction and spectral unmixing use only the spectral information contained in the hyperspectral data. In this paper, we introduce a novel method for spatial-spectral endmember extraction which incorporates texture features in the quantification of spatial information (jointly with spectral information). Experimental results with simulated and real hyperspectral data sets indicate that textural information could assist the extraction of spectral endmembers, although a challenging issue still remains: how to combine the final set of endmember candidates (obtained by merging the individual sets of candidates found using spectral, textural and joint spectral-textural information) in order to provide a relevant final solution.