Nonnegative matrix factorization with regularization and sparsity-enforcing terms

The aim of this paper is to present several multiplicative algorithms for nonnegative matrix factorization. We show how to obtain such algorithms in the case where non-negativity and flux conservation constraints are imposed, and how to regularize such problems by introducing smoothness or sparsity properties. Application to hyperspectral imagery is finally considered.