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Author Topic: Deconvolution sharpening revisited  (Read 83758 times)
Fine_Art
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« Reply #240 on: October 12, 2011, 02:05:54 AM »
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Here is a very fast sharpen of a crop. 2 ground squirrels printscreen to paint.

This took maybe 3 seconds due to the small size. A full 16MB picture would be about a minute. Its a multi-threaded 64 bit program.
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jguentert
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« Reply #241 on: January 09, 2012, 03:30:41 PM »
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For all those who are interested in deconvolution like me this may be interesting: I'm still searching for a convincing solution for the Mac. I bought Topaz InFocus but I am not satisfied with it. I would pay a lot to get the not perfect but easy to use Focus Magic updated for CS 4 or 5 (without the need of Rosetta) or Caron with a more convenient Mac interface.

But meanwhile I found sth. relatively new in this special field: Back In Focus Currently implemented algorithms: Unsharp masking (fast and full), Wiener finite and infinite impulse response, Richardson-Lucy (with a thresholding variant), Linear algebra deconvolution.

"Back In Focus" is absolutely not for beginners. It took me some days to learn how to use it and here's room for improvement. But once you got how to use it you'll get better pictures.

http://www.metakine.com/products/backinfocus/

Example:

« Last Edit: January 09, 2012, 03:52:41 PM by jguentert » Logged
BernardLanguillier
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« Reply #242 on: January 09, 2012, 05:01:08 PM »
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"Back In Focus" is absolutely not for beginners. It took me some days to learn how to use it and here's room for improvement. But once you got how to use it you'll get better pictures.

http://www.metakine.com/products/backinfocus/

Thanks for the link, it sounds interesting.

Would you say its main strenght is to further improve the detail of sharply focused images, or it is more devoted to recovering blurred images (hand shake, focus softness,...)?

Cheers,
Bernard
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« Reply #243 on: January 09, 2012, 05:47:10 PM »
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Thanks, I'll give this a whirl.    I do like Caron, much better than topaz.    I know there also must be some tools for imageJ but haven't tried any.  Has anyone tested any deconvolution plugins for imageJ that they like?

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jguentert
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« Reply #244 on: January 09, 2012, 06:03:36 PM »
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It's definetly devoted to recovering blurred images.
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BernardLanguillier
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« Reply #245 on: January 09, 2012, 07:04:01 PM »
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It's definetly devoted to recovering blurred images.

Thanks for the feedback.

Cheers,
Bernard
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« Reply #246 on: January 09, 2012, 09:35:01 PM »
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Well, this is not exactly intuitive and at least some of the routines run very slow. 
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sjprg
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« Reply #247 on: December 27, 2012, 02:53:41 PM »
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Hey guys, has the interest waned again, or have we beat the subject to death? I don't have the math to contribute but I do have an interest in following the discussion.
Regards
Paul
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walter.sk
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« Reply #248 on: December 27, 2012, 08:54:01 PM »
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Back In Focus Currently implemented algorithms: Unsharp masking (fast and full), Wiener finite and infinite impulse response, Richardson-Lucy (with a thresholding variant), Linear algebra deconvolution.

I tried downloading it but couldn't install it on a Windows machine.  Is it only for MAC?
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sjprg
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« Reply #249 on: December 28, 2012, 01:40:01 AM »
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MAC only
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walter.sk
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« Reply #250 on: December 28, 2012, 11:32:49 AM »
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MAC only
Hmmm!  Oh, well.  Now, if they would only upgrade Focus Magic to 16Bit or more.  With all of its faults I had found it the best for "capture sharpening."
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bjanes
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« Reply #251 on: December 28, 2012, 12:54:12 PM »
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Hmmm!  Oh, well.  Now, if they would only upgrade Focus Magic to 16Bit or more.  With all of its faults I had found it the best for "capture sharpening."

I see that Focus Magic will have a beta for 64 bit windows in January 2013 and for the Mac in March 2013. AFAIK the old version does support 16 bit files, but I have not used it for some time since I upgraded to 64 bit windows. One can use it with 32 bit Photoshop, but it is a pain to switch back and forth between 32 and 64 bit.

Bill
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sjprg
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« Reply #252 on: December 28, 2012, 01:08:08 PM »
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I write them about 4 times a year requesting an update. They keep responding "we are too busy on other projects"
Hopefully someday they will give us an updat. They had the best available. In the meantime I use ACR 7.3 at
amount=0, radius=.5, detail=100 which seems to work very well.
Regards
Paul
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Fine_Art
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« Reply #253 on: March 16, 2013, 02:12:05 PM »
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I think you are fixating on the particular implementation (that Bart used) rather than considering the method in general.  Typically most of the improvement to be had with RL deconvolution comes in the first few tens of iterations, and the method can be quite fast (as it is in RawTherapee, FocusMagic, and RawDeveloper, for instance).  A good implementation of RL will converge much faster than 1K iterations.  It's hard to say what is sourcing the ringing tails in Bart's example; it could be the truncation of the PSF, it could be something else.  I would imagine that the dev team at Adobe has spent much more time tweaking their deconvolution algorithm than the one day that Bart spent working up his example.

But I would ask again, why do you want to throw dirt on deconvolution methods if you are lavishing praise on ACR 6.1?

This thread was linked in a current thread so I am bringing up my 2 bits years later.

I have been using deconvolution for years. Sometimes in an image I can find something that lets me use the custom PSF function in images plus. When this happens a single cycle of deconvolution dramatically improves the image blur. Further cycles using that PSF actually dont work better than a regular function like a gaussian for the obvious reason that that PSF no longer matches the state of the image. To really use a good custom you have to modify it each cycle as the image is improving.

Using a 1000 cycle approach is fine if you use a very mild under-correction wanting it to converge to something. I have never gone more than 250 cycles with a mild function because I simply do not see further improvements. I mostly use 3x3 gausssian for example even If I know it needs a couple cycles with a 7x7. The artifact damage to other parts of the image is much less.

My rule of thumb is if I cant do it with 50 cycles I am using the wrong function. Usually I just use 10 cycles. Sometimes less, I have images where I stop after 3 cycles of a 3x3 gauss, the lightest the program runs.
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BartvanderWolf
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« Reply #254 on: March 16, 2013, 04:12:47 PM »
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This thread was linked in a current thread so I am bringing up my 2 bits years later.

Hi Arthur,

The thread is as relevant today as it was when it was started. No problem with people adding to it. RawTherapee just a few days ago improved the speed of its RL sharpening implementation, and FocusMagic is beta testing the long overdue 64-bit version of their plugin. So the subject is very much alive.

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I have been using deconvolution for years. Sometimes in an image I can find something that lets me use the custom PSF function in images plus. When this happens a single cycle of deconvolution dramatically improves the image blur. Further cycles using that PSF actually dont work better than a regular function like a gaussian for the obvious reason that that PSF no longer matches the state of the image. To really use a good custom you have to modify it each cycle as the image is improving.

That depends on the algorithm used, but in particular the Richardson-Lucy deconvolution is an iterative algorithm that internally iterates to optimize certain parameters. It's not simply a repetition of the same deconvolution with the same PSF.

To demonstrate that multiple iterations do serve a purpose, especially with a low noise image, I've created the following example:

Here is the test target that was used for the following demonstration:

Here is the sigma=1.0 PSF that was used to convolve (blur) the image, and then deconvolve the blurred 'star' version.

Click on the image to get a higher accuracy 32-bit floating point TIFF version of the PSF

Here is the convolution result:

Here is a RL deconvolution result after 10 iterations, resolution has improved:

Here is a RL deconvolution result after 100 iterations, it has better resolution:

Here is a RL deconvolution result after 1000 iterations, it has even better resolution, however not all resolution could be restored.
When the blur reduces the image detail to zero contrast, then all is lost:

The RL implementation used was from PixInsight Version 1.8, and I used the unregularized RL version, because there was no noise in this artificial (CGI) image.

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My rule of thumb is if I cant do it with 50 cycles I am using the wrong function. Usually I just use 10 cycles. Sometimes less, I have images where I stop after 3 cycles of a 3x3 gauss, the lightest the program runs.

Often, 10 or 20 iterations are plenty, especially with some noise in the image and a less than perfect PSF (which is the common situation). I do see a benefit in 'rolling your own PSF', because it allows to make more accurate versions than the few default ones that many programs offer. Since Gaussian shaped PSFs are often close to ideal, my PSF generator tool can assist in producing a number of PSFs to choose from. The numerical data can be copied and pasted into a text file, which e.g. ImageJ can import as a space separated text image file, for those applications that take a PSF image as input. Others will need to copy and paste the data into dialog boxes.

Cheers,
Bart
« Last Edit: March 16, 2013, 04:27:17 PM by BartvanderWolf » Logged
Fine_Art
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« Reply #255 on: March 16, 2013, 10:07:01 PM »
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Bart I understand the role of iteration. What I am referring to is "custom" PSFs not standard distributions. A custom to me is something selected from the image.

Your demonstration is running a math function on a chart then reversing it with iterations of a standard Gaussian. The problems we have out in nature are imperfect lenses, front focus/back focus, tripod vibration, shutter vibration. The FF/BF component would be handled nicely by a Gaussian. The rest need something else which you can only find in the image itself. If you do select some strange shape from the image it will make the blur better fast or not help much. If it does help you need to switch to something else soon or it just starts to make another mess.
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Fine_Art
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« Reply #256 on: March 16, 2013, 10:28:17 PM »
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Here is an example ofwhere I could find a "custom" PSF.

There was wind against the building while the fireworks were going. There was also the big booms of the larger shells. Looking around through the full size images I can probably find lights that should be perfectly round. many will be odd shapes from being reflected in glass. If I make a good selection I can remove almost all the problems of the shot.
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Fine_Art
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« Reply #257 on: March 16, 2013, 10:58:39 PM »
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So in that shot I found some rich person had been useful enough to get a chopper to watch the Canada day fireworks. I just watched them from my balcony Cheesy.
In the first 200% zoom you can see the oblong PSF of the chopper's safety lights. I pick that as a test "custom" then cut a piece out of the rest of the shot to test it on.
In the second screenshot you can see the impact of 2 cycles. The first cycle was an improvement. The second is starting to make halo edges. If I keep goin it will make a mess.
So if that really was a better PSF than another I find in the shot I would re-sample it after the cycle. It would be a new different PSF.

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Fine_Art
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« Reply #258 on: March 16, 2013, 11:56:52 PM »
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Here is a the original unsharpened in the middle
10 cycles  of gaussian 5x5 on the left
custom on the right.
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rnclark
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« Reply #259 on: January 13, 2014, 10:07:59 PM »
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My first post.  I was sent this link by someone else, and as I was referenced in the post that started this thread, I thought I would add to it.

My web page on image deconvolution referred to in the first post is: http://www.clarkvision.com/articles/image-restoration1/
and has been updated recently.

I have added a second page with more results using an image where I added known blur and then used a guess PSF to recover the image.  This is part 2 from the above page:
http://www.clarkvision.com/articles/image-restoration2/

Regarding some statements made in this thread about how one can't go beyond 0% MTF, that is true if one images bar charts.  But the real world is not bar charts.  MTF is a one dimensional description of an imaging system.  It only applies to parallel spaced lines and only in the dimension perpendicular to those lines.  MTF limits do not apply to other 2-D objects.  For example, stars are much smaller than 0% MTF yet we see them.  Two stars closer together than the 0% MTF can still be seen as an elongated diffraction disk.  It is that asymmetry and a known PSF of the diffraction disk that can be used to fully resolve the two stars.  Extend this to all irregular objects in a scene, whether it be splotchy detail on a bird's beak, feather detail, or stars in the sky, deconvolution methods can recover a wealth of detail, some beyond 0% MTF.

I have been using Richardson-Lucy image deconvolution on my images for many years now, both astro images and everyday scenes.  It works well and I can consistently pull out detail that I have been unable to achieve with smart sharpen or any other method.  Smart sharpen is so fast that it can't be doing more than an iteration (or a couple if done in integers). I would love to see a demonstration by those in this thread who say smart sharpen can do as well as RL deconvolution.  On my web page, part 2 above, I have a link to the 16-bit image (it is just above the conclusions).  You are welcome to download that image and show something better than I can produce in figure 4 (right side) on that page.  Post your results here.  I would certainly love to see smart sharpen do as well, as it would speed up my work flow.

Thanks for the interesting read.  And a special hi to Bart.  I haven't seen you in a forum in years.

Roger Clark
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