Hi Terry,

haven't been reading the list for some time, but thought I reply anyhow.
I'm a bit puzzled that when using a 512x512 instead of a 256x256 you get
(really?) bad results when you get reasonable ones for the smaller one, even
if it is contained in the larger one.  With the concerns I had about (too
strong) variations of the PSF over the FOV you still should get a reasonably
reconstructed image in the small subpart that was used to derive it...

That raises one or two questions on how you are doing things.  Does your PSF
go to 'real' space, or are you doing everything in fourier space?
If you just had two images (sharp and unsharp), FFT them, build the quotient
and call that PSF, then apply that (Fourier) PSF to the unsharp image than
indeed this will work perfectly - but only for exactly this image, and it even
doesn't depend on wether you align it or not (the PSF can/will also contain
image shift information).

The other thing is, how did you extend the small PSF to the large FOV?  By
padding with zeros?  If this is not done properly things can go bad, too (FFT
is normally sorted in a wrapped order).

One idea what to try would be take the 512 field, divide it into 4x4 fields of
128, derive PSFs in these subfields, average them and apply the average
(propperly padded) to the large image and see what that does.  (The idea is
that if you have only two images to create the PSF it will contain a lot of
noise information that gets smoothed out that way and make the PSF more
general). 

Another one would be to FFT the PSF back to normal space, have a look at it
and maybe run some filters on it (median to remove singular peaks etc.).  The
abovementioned averaging could also be done on those PSFs...

Cheers,

  Pit

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