Hello Matthew,
On Sat, 05 Oct 2013 00:48:50 +1000, Matthew Petroff <[email protected]>
wrote:
Terry,
I modified the MATLAB script to only run their algorithm and use the
provided motion blur blur kernel on a full size image. Here are the
results
when run on an 18MP photo I had:
Original:
http://i.imgur.com/rRwaKbc.jpg
Blurred:
http://i.imgur.com/NyGg6JN.jpg
Deconvoluted:
http://i.imgur.com/fCeOTGy.jpg
The results look quite good.
Almost all the examples I have seen of non-blind deconvolution, where the
example image is blurred by a given kernel and then de-blurred using that
kernel, come out looking good.
The script takes the original image, applies the blur kernel, adds
Gaussian noise to both the blurred image and the blur kernel, and then
runs the
deconvolution. It took an hour and a half, maxing out all four cores of
my 4.2GHz Ivy Bridge processor.
I'm not surprised, that is a big image and it is quite an intensive
process.
If you have any images you want me to test,
I'd be happy to do so. We just need a good way to estimate an image's
blur kernel.
This is the difficult bit. I have worked with a few different approaches
to estimating the blur kernel. It has been a while now since I was deeply
engrossed in this stuff, so I'll have to have a look back in my archives
and refresh my memory a tad.
Give me bit of time, and I'll see if I can get a reasonable kernel for my
test image.
Cheers,
--
Regards,
Terry Duell
--
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