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In this paper, we investigate the use of the watershed transformation for integrating spatial and spectral information in the process of endmember extraction for spectral unmixing of hyperspectral images. The proposed approach is presented as a preprocessing module designed to automatically select a small subset of pixels containing potentially relevant candidates from both spatial and spectral point of view. Dimensionality reduction is required. The idea is to use the morphological watersheddoi:10.1109/igarss.2010.5649373 dblp:conf/igarss/ZorteaP10 fatcat:jgpf752yanbqbf4ydujmechq5e