Sharpening old files really can make a difference

Read more about “point spread function”.

The Richardson–Lucy algorithm , also known as Lucy–Richardson deconvolution , is an iterative procedure for recovering an underlying image that has been blurred by a known point spread function. It was named after William Richardson and Leon Lucy, who described it independently.[1][2]

Personally, for my Fujifilm X-T2 filed I prefer the look of USM over RL. RL seems to introduce artifacts more quickly in my opinion, but maybe I don’t know how to use RL. For USM I use a low radius (0.4 to 0.45) and high amount (800 to 1000).

For my X-T20 (which is the same sensor and processor) I find that moving the contrast threshold slider up and lowering the radius helps with the artifacts. I also often lower the the amount to somewhere between 70 and 85.
Basically, this means that defaults are too high and things need to be dialed back a few notches.

One thing that has puzzled me is why the two algorithms (USM and RL) are an either or scenario and can’t be stacked. My feeble mind’s logic says that a little bit of each would give the best of both.
Is there a technical reason why they can’t (or shouldn’t) be stacked or is it just how it was coded?

I never tried stacking them (one one top of the other), but I would guess that leads to artifacts when not using blend masks to decide where one or the other will be used.

After I posed my question, I did some Googling and found this:

http://www.clarkvision.com/articles/image-restoration2/index.html

Image deconvolution iterations reach a plateau and then only seem to enhance noise. In my experience it is best to find that plateau and stop the iterations just as the plateau is reached. Then run unsharp mask or smart sharpen on that result and try additional image deconvolution iterations using a smaller point spread function. A final unsharp mask on that result can help perceived sharpness. The multiple combinations of image deconvolution and unsharp mask (edge contrast enhancement) produces the best results in my experience with hundreds of images.

Hey, its on the internet so it must be true, right? :thinking:

Seriously though, it looks like something worth investigating when I have spare time. I guess I can export the file from RT and then reopen it?

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Yes, that’s a proper way to test it.

I have read conflicting accounts on this topic. Recent papers seem to indicate that stacking and iterating doesn’t improve sharpness (or acutance) all that much because artifacts tend to overtake the benefits very quickly. It might be better to optimize the parameters and perform the processing once. The real answer is that it depends, or the algorithm could be extended to adapt to more scenarios.

Personally, although RT has powerful tools, I prefer doing some custom sharpening (which is time and brain consuming), or not doing any at all. But that is just me.

Now I just need the free time – and have the computer free at the same time. (Its not easy sharing a computer with teenagers :scream:)

Get them interested. Nothing more satisfying than having others do your lab tests, for free!

You can sort of stack them by using post-resize sharpening.

Correct, but you still have to open the resulting file as you can’s see the pr-sharpening in preview.

Can I resize to 100%?

Yes – just set the bounding box to something huge, like 10000x10000, and disable upscaling.

OK, my daughter got phone call so I swooped in and snagged some PC time. I did my best job sharpening an image with RL, then saved it as a 16 bit tiff. I reopened the tiff with RawTherapee and tried my best with USM. I was only able to get maybe a hair sharper before artifacts set in.

While its only a sample size of 1, my preliminary conclusion that RT’s algorithm for USM cannot improve an image that was processed through its RL algorithm.

Anyone else care to try?

:eagle:

Interested in seeing your results and pp3 files.

DSCF4498.RAF (24.5 MB)
DSCF4498.RAF.pp3 (11.8 KB)

I challenge everyone to take the .tif and improve on it with just USM.

With letters it’s usefull to experiment with also enabling “Edges” starting with weak settings (say it.1, quant.20) … I almost always find the result improved against without …

BTW … the default settings are too strong … :frowning:

The default settings of Edges?

Ingo, yes … I find 2, 50 is too strong.