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Proceedings Paper

A comparison of algorithms to compute the positive matrix factorization and their application to unsupervised unmixing
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Paper Abstract

This paper presents a comparison of different algorithms to compute the constrained positive matrix factorization and their application to the unsupervised unmixing problem. We study numerical methods based on the Gauss-Newton algorithm, the Seung-Lee approach, the Gauss-Seidel algorithm, and penalty methods. Preliminary results using a Hyperion image from southwestern Puerto Rico presented. Algorithms will be compared in terms of their convergence performance, and quality of the results.

Paper Details

Date Published: 8 May 2006
PDF: 11 pages
Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 623326 (8 May 2006); doi: 10.1117/12.667977
Show Author Affiliations
Yahya M. Masalmah, Univ. of Puerto Rico/Mayagüez (United States)
Miguel Vélez-Reyes, Univ. of Puerto Rico/Mayagüez (United States)


Published in SPIE Proceedings Vol. 6233:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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