[crazygringo]

> You can't fix it all computationally.

Can't you? If you're dealing with known hardware, then you can apply a deconvolution. Blurring can literally be undone, people do it all the time. It's harder when you have to estimate the kernel, but much easier when you already know the lens's exact properties. Also when you apply it directly to RAW data.

So not exactly sure which information you're referring to you when say information is being lost?

Sure artifacts can be introduced from noise, etc., but that's all just tradeoffs. If a simpler lens is letting in more light, or you put money towards the sensor rather than the lens, the end result may well be better, no?

[proudfoot]

You don't have the exact kernel, if you're even slightly wrong you can end off being worse off. You'll have very significant variation in lower quality optics.

And there's a variety of sharpening tools that claim to do this! DxO is a company that sells a raw processor for precisely this purpose. People still buy better lenses.

[hatsunearu]

If you have depth information blurring can be undone theoretically, but you don't.

[karmakaze]

I think you might be able to do a good job if you had a depth map of the image. You could use ML to guess them. Computation without that treats incident angles that vary by the distance ratios as the same.

[91aintprime]

Some blurring is like pixelization