The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

Yahya M. Masalmah; Miguel Vélez-Reyes

doi:10.1117/12.719779

7 May 2007 The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

Yahya M. Masalmah, Miguel Vélez-Reyes

Author Affiliations +

Proceedings Volume 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII; 65650B (2007) https://doi.org/10.1117/12.719779
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Citation Download Citation

Yahya M. Masalmah and Miguel Vélez-Reyes "The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization", Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650B (7 May 2007); https://doi.org/10.1117/12.719779

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