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

Yahya M. Masalmah; Miguel Veléz-Reyes

doi:10.1117/12.779444

11 April 2008 A full algorithm to compute the constrained positive matrix factorization and its application in unsupervised unmixing of hyperspectral imagery

Yahya M. Masalmah, Miguel Veléz-Reyes

Author Affiliations +

Proceedings Volume 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV; 69661C (2008) https://doi.org/10.1117/12.779444
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

Citation Download Citation

Yahya M. Masalmah and Miguel Veléz-Reyes "A full algorithm to compute the constrained positive matrix factorization and its application in unsupervised unmixing of hyperspectral imagery", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661C (11 April 2008); https://doi.org/10.1117/12.779444

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