Algorithm taxonomy for hyperspectral unmixing

Nirmal Keshava; John P. Kerekes; Dimitris G. Manolakis; Gary A. Shaw

doi:10.1117/12.410362

23 August 2000 Algorithm taxonomy for hyperspectral unmixing

Nirmal Keshava, John P. Kerekes, Dimitris G. Manolakis, Gary A. Shaw

Proceedings Volume 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI; (2000) https://doi.org/10.1117/12.410362
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Nirmal Keshava, John P. Kerekes, Dimitris G. Manolakis, and Gary A. Shaw "Algorithm taxonomy for hyperspectral unmixing", Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); https://doi.org/10.1117/12.410362

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