[Show abstract][Hide abstract] ABSTRACT: This paper offers a new point of view on component separation, based on a model of additive components which enjoys a much greater flexibility than more traditional linear component models. This flexibility is needed to process the complex full-sky observations of the CMB expected from the Planck space mission, for which it was developed, but it may also be useful in any context where accurate component separation is needed.
[Show abstract][Hide abstract] ABSTRACT: We describe an ICA method based on second order statistics which was originally developed for the separation of components
in astrophysical images but is appropriate in contexts where accuracy and versatility are of primary importance. It combines
several basic ideas of ICA in a new flexible framework designed to deal with complex data scenarios. This paper describes
our approach and discusses its implementation in terms of a library of components.