Possibly a new deconvolution module for Darktable

Software darktable
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I’m wondering what the timeline for inserting this into dt might be? Not a hard date but a “maybe version x” date.

I have a photo in which some leaves moved slightly, enough to give them a bit of a blur. This module might help. I really like the photo and am sorry that, with that particular point and shoot camera, I couldn’t increase the shutter speed so I prayed that the leaves wouldn’t move too much (they didn’t too much but enough for me to wish that they hadn’t at all).

Thanks

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Read this:

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I read through this whole thread. Very interesting. Has anything more been done with this? Anything in dt yet? While having the best implementation, of course, is great, if it is too heavy to do in dt that has to show quickly the results on screen then even a less than ideal implementation that works pretty well would be nice. And maybe a heavier, slower option.

Eric Chan says that Lightroom and Photoshop in some cases use deconvolution when sharpening:

Yes Photoshop’s Smart Sharpen is based on deconvolution (but you will need to choose the “More Accurate” option and the Lens Blur kernel for best results). Same with Camera Raw 6 and Lightroom 3 if you ramp up the Detail slider.

That is from an old thread on the Luminous Landscape site. Unfortunately, it seems the website is mostly behind a firewall now so the link to that thread I have no longer works:

http://www.luminous-landscape.com/forum/index.php?topic=45038.msg377910#msg377910

This guy:

Principal Scientist and “Mad Man” Eric Chan Discusses His Role in Improving Photoshop

https://blog.adobe.com/en/2013/07/12/principal-scientist-and-mad-man-eric-chan-discusses-his-role-in-improving-photoshop.html#gs.ifkhlv

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Exposure-invariant guided filter has been finished by @rawfiner and myself today, which is a requirement for the “image doctor” module that implements the ideas developed here, but in a faster way.

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Hi,

Interesting. Any reference (or pointer, if you prefer)?

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You can take a look here, though I wrote this document quite a long time ago so I should update it: GitHub - rawfiner/eigf
And on the PR: Exposure-independent guided filtering for tone-equalizer by rawfiner · Pull Request #6444 · darktable-org/darktable · GitHub
though the text on the PR is also a bit outdated.

Basically, we do a standard guided filter, except:

  • we use gaussian blurs instead of box blur
  • we normalize the variance by the geometric mean of the pixel value and the average (this makes the filter exposure invariant as this ratio does not change when exposure changes)
  • we removed the blur on “a” and “b”, as it gave halos or big areas without smoothing near the edges, and it seemed impossible to fix this blur, although we tried many things (including approach from anisotropic guided filtering paper)

Also, the implementation uses downscaling to speedup variance and average computation, but it uses downscaling in a slightly different way than what was proposed with standard guided filter: at the end we upscale the variance, covariance and averages and compute a and b at full resolution, instead of upscaling a and b (which gave artefacts due to the fact that we removed the blur on a and b)

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Congrats. Comports with my independent study. Looking forward to seeing what you settle on because I am undecided on which ideas to discard or keep. I have too many. :slight_smile:

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Thank you. I will look at your image doctor thread.

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One very minor note is that there is a paper that names its method as EIGF (Enhanced Input Guided Filter) but is something different (not as good as our methods). Up to you whether you want to differentiate by choosing a different acronym.