News from here... I'll implement a different approach to this, called Super-resolution. In a nutshell, it is a combination of registration, integration, deconvolution and noise reduction.
Right now I'm working on a new automatic registration method, that can be applicable to any kind of images, but that only calculates rotations and shifts. A local registration algorithm may be used on top of this. The benefit from this rigid technique, is that it should be fast and more accurate than other methods (for example, fourier analysis). Also, this should be enough for long exposure frames, where distortions frames are irrelevant. A more local approach should be used for solar, lunar or planetary images, that may work over the rigid solution.
After the registration routine, I must write the deconvolution/noise reduction steps, that use all the data from the series, and yields an optimised solution.
I'll post the modules somewhere as soon as I have something to try with real data. I'll be quite overloaded with work at the university the following weeks, so I may release a first version in July.