Doesn't time fly, it's 'a bit more' than some years by now.
BTW, I've added a couple of drum scanners, a Nikon 8000 and a V700 to my collection (besides the Minolta 5400, Epson 2450 and Microtek 120).
IMHO there are 3 obvious fundamental candidates:
- A mix of Gaussians
- Defocus blur (DOF related or plain OOF)
- Diffraction dominated
What about segmenting the image and applying a different PSF to each relevant portion?
I was talking about that with ejmartin in the RT forum.
Real lenses have different issues near center, at borders and at corners.
Maybe trying to compensate all different effects and aberrations with a single PSF across the whole frame is asking too much.
Example: a fast lens shooting at large aperture may show strong coma at the edges a just some spherical aberration at the center.
I'm in the process of programming a "PSF generator" application
Now, this is such a wonderful idea!!
I'm driving crazy trying to write down discrete kernels for my tests.
In this thread I posted an image crop that has the diffraction of f/32 added
Here we have a couple of tests of mine.
Please note that since my dirty little app only manages gray images at this time, I had to convert to Lab and deconvolve Lightness only.
First test: RT Gaussian approximation (3x3 kernel).
Radius (sigma) = 1.2, 2000 iterations, no damping.
Your deconvolution has more hi-freq details, but more ringing. See the angled white bar near the bottom of the tree.
Second test: same kernel, but I tried a special "turbo" mode, modifying the R-L implementation so that I can use a very narrow Gaussian (small sigma) and very few iterations.
radius = 0.35, 60 iterations, no damping.
This method is very fast but really "nervous", can diverge easily.
EDIT: Mmmm, I dont' understand, why are my images downsized? I'm sure the original links are full-res!
Well, here you can find direct http links:http://img840.imageshack.us/img840/3705/cropdiffractionrtlr.jpghttp://img830.imageshack.us/img830/4939/cropdiffractionrtlrturb.jpg