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Many algorithms have been recently proposed in order to solve the unsupervised hyperspectral data unmixing problem, under the linear spectral mixing model assumption (LMM). The main approaches can be roughly gathered in three groups : non-negative matrix factorization (NMF), geometrical algorithms and Bayesian estimation. The choice of an adequate algorithm can be somewhat tricky for the analysis...
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