  Coupled structured matrix factorization (CoSMF) for hyperspectral
super-resolution (HSR) has recently drawn significant interest in hyperspectral
imaging for remote sensing. Presently there is very few work that studies the
theoretical recovery guarantees of CoSMF. This paper makes one such endeavor by
considering the CoSMF formulation by Wei et al., which, simply speaking, is
similar to coupled non-negative matrix factorization. Assuming no noise, we
show sufficient conditions under which the globably optimal solution to the
CoSMF problem is guaranteed to deliver certain recovery accuracies. Our
analysis suggests that sparsity and the pure-pixel (or separability) condition
play a hidden role in enabling CoSMF to achieve some good recovery
characteristics.
