In this paper, we introduce a set of taxonomies that hierarchically organize and specify algorithms associated with hyperspectral unmixing. Our motivation is to collectively organize and relate algorithms in order to assess the current state-of-the-art in the field and to facilitate objective comparisons between methods. The hyperspectral sensing community is populated by investigators with disparate scientific backgrounds and, speaking in their respective languages, efforts in spectral unmixing developed within disparate communities have inevitably led to duplication. We hope our analysis removes this ambiguity and redundancy by using a standard vocabulary, and that the presentation we provide clearly summarizes what has and has not been done. As we shall see, the framework for the taxonomies derives its organization from the fundamental, philosophical assumptions imposed on the problem, rather than the common calculations they perform, or the similar outputs they might yield.
Date of creation, presentation, or exhibit
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Keshava, Nirmal; Kerekes, John; Manolakis, Dimitris; and Shaw, Gary, "An algorithm taxonomy for hyperspectral unmixing" (2000). Accessed from
RIT – Main Campus