A Full Algorithm to Compute the Constrained PositiveMatrix Factorization and its Application in UnsupervisedUnmixing of Hyperspectral Imagery

摘要

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.