Hi guys,
I recently got to finally try DT 4.6 neural restore and it’s great! So to what better use we could put it than to breathe new life into old cameras? Off the shelf comes the Pentax K10D - famouse image quality, but max. ISO 1600, and that is a bit noisy. Can we remove the noise through AI? Turns out we can – but with a catch!
In this image, left-to-right, top-to-bottom, see the results of:
- no denoising
- denoise (profiled)
- neural restore denoise after the pipeline
- neural restore raw denoise
Clearly, each result a bit better than the previous, although there isn’t that much difference between conventional denoise (profiled) and NR denoise after processing. NR raw denoise on the other hand is a lot better, at least in the area of the pouch (it’s also a bit more aggressive, but I think it really is better).
But, alas! It amplifies hot pixels a lot, so much that they can no longer be removed by the automatic hot pixels filter, and at the same time, are clearly distracting. And the 20-year-old K10D has a lot of them! So I would have to use retouch on each one.
But as I understand it, there is no way to run any filter or processing step before the NR raw denoise, or is there? Even if I export minimal processing without hot pixels as a TIFF, that’s not RAW anymore, so no raw denoise.
Another idea would be to train a denoising model that removes hot pixels, but I am not sure how to go about that and if it’s feasible.
Any thoughts on that matter? FWIW, I will also upload the RAW if anybody wants to inspect a sample (license: public domain).
IMGP2101.DNG (16.1 MB)
