SNIP
Are you still investigating PSF-based deconvolution?
Yes, the status is as follows.
Intro.
It is preferable to use a slanted edge target, as the image of it will
allow to produce an over-sampled edge profile (=Edge Spread Function
or ESF). The first difference/derivative of that one dimensional ESF
is called a Line Spread Function (LSF). An LSF is identical to a 1D
integral of a 2D Point Spread Function (PSF).
Since I have not found a (generally) simple to implement method of
creating a 3D PSF out of a 2D LSF, I've taken the opposite approach.
I've created a quick-and-dirty Excel Spreadsheet that builds a
composite* Gaussian PSF, and then takes an approximate 1D integral of
it, thus producing its LSF.
This is then compared to the actual edge's LSF (calculated from the
copy&pasted Imatest output), and by using the "Solver" add-in the
squared error is minimized.
* Composite meaning that I actually take multiple (currently 3)
Gaussian PSFs with different Standard Deviations and weights (which is
a suggestion I found in an Italian paper). Other functions could be
modeled, but Gaussians have several useful properties.
I've found a new way to implement a L-R type deconvolution,
maybe! Still in the very early phase of the study.
Interesting, as it was one of my main concerns for sharing this info.
The results of the approximated PSF can be used in a variety of
programs that use built-in Deconvolution functions based on an input
kernel, but probably only few of this group's audience will have
access to such a program.
Therefore, I've recently also added to my spreadsheet a High-Pass
filter kernel generator that does a similar Job, but much faster.
After-all deconvolution in Frequency space is identical to convolution
in the Spatial domain, and with simple smallish kernels it's just
faster to simply convolve.
The Custom Plug-in from
<
http://www.reindeergraphics.com/free.shtml#customfilter> allows to
use a (8 or) 16-bit/channel 7x7 input kernel in Photoshop (which is
more accurate than Photoshop's 5x5 Custom kernel).
<
http://www.reindeergraphics.com/free.shtml#selectedge> will allow the
creation of an edge mask in Photoshop.
The main difference between e.g. adaptive RL restoration and High-Pass
filtering is that RL restoration will allow to extract a bit more info
with better S/N ratio, but at the cost of a *much* longer processing
time. Adding an Edge-Mask to the High-Pass filtered layer will make
some of the differences between methods smaller.
What's more, in the context of this newsgroup, a small (per scanner)
table could be used in VueScan to allow the calculation of the
'optimal' HP 'sharpening'-filter. Only the STDEV and Weight of the
composite Gaussians needs to be recorded, all HP convolution kernel
values can be calculated from that (possibly separable into X and Y
directions for a faster execution, but I yet need to test that).
Bart
P.S. If your email address is valid, I could send you a copy of my
(beta version) spreadsheet for evaluation.
