An algorithm taxonomy for hyperspectral unmixing

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Title: An algorithm taxonomy for hyperspectral unmixing
Author: Keshava, Nirmal; Kerekes, John; Manolakis, Dimitris; Shaw, Gary
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.
Description: "An Algorithm taxonomy for hyperspectral unmixing," Proceedings of Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI. International Society of Optical Engineers. Held at AeroSpace in Orlando, Florida: 24-26 April 2000. Copyright 2000 Society of Photo-Optical Instrumentation Engineers. This paper was published in Proceedings of Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, SPIE vol. 4049 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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Date: 2000-04-24

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