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Unsupervised spectral unmixing by minimum-volume-constrained non-negative matrix factorization (MVC-NMF)

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MVCNMF

The Minimum Volume Constrained Non-negative Matrix Factorization (MVC-NMF) is an unsupervised endmember extraction algorithm. It is designed for highly mixed image data.

Usage

run "nmf_test.m"

Contributors

Lidan Miao, Hairong Qi (hqi@utk.edu), EECS, University of Tennessee, Knoxville

Reference

L. Miao, H. Qi, "Endmember extraction from highly mixed data using minimum volume constrained non-negative matrix factorization," IEEE Transactions on Geoscience and Remote Sensing, 45(3):765-777, March 2007.

The paper received the Highest Impact Paper Award in 2012 from the IEEE Geoscience and Remote Sensing Society.

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Unsupervised spectral unmixing by minimum-volume-constrained non-negative matrix factorization (MVC-NMF)

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