I took another break from vacation to meet up with Marshall and Lang in Princeton, where Marshall is visiting. We wrote (or re-wrote) an image differencing code that finds the best mutual convolution kernel by least-square fitting in a very general (free) basis. It works well, but is not super-fast. Hey reader: What are the best test cases for this? And how do we know if we have beaten or matched the industry standard?
If you can make an HST image look like a MIPS 24- or, more grotesquely, 160-micron image, then you're on to something.
ReplyDeleteIn terms of "industry standard" there's this:
http://dirty.as.arizona.edu/~kgordon/mips/conv_psfs/conv_psfs.html
and this:
http://www.astromatic.net/software/psfex
among others, I'm sure.