2011-05-26

image differencing for lensing

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?

1 comment:

  1. If you can make an HST image look like a MIPS 24- or, more grotesquely, 160-micron image, then you're on to something.

    In 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.

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