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Proceedings Paper

A full algorithm to compute the constrained positive matrix factorization and its application in unsupervised unmixing of hyperspectral imagery
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Paper Abstract

This paper presents a full algorithm to compute the solution for the unsupervised unmixing problem based on the positive matrix factorization. The algorithm estimates the number of endmembers as the rank of the matrix. The algorithm has an initialization stage using the SVD subset selection algorithm. Testing and validation with real and simulated data show the effectiveness of the method. Application of the approach to environmental remote sensing is shown.

Paper Details

Date Published: 11 April 2008
PDF: 12 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661C (11 April 2008); doi: 10.1117/12.779444
Show Author Affiliations
Yahya M. Masalmah, Univ. of Turabo (United States)
Miguel Veléz-Reyes, Univ. of Puerto Rico at Mayagüez (United States)


Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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