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▲Show HN: Deconvolution – a Rust image deconvolution and restoration crate (github.com)

33 points by rmi0 4 days ago | 5 comments

esafak 2 days ago [-]

Nice work. Old skool methods at this point. You could add some neural methods but then you'd lose any performance benefits of Rust and might as well use the richer Python ecosystem.

srean 2 days ago [-]

I am a little wary of the new school denoisers.

https://news.ycombinator.com/item?id=48263398

https://news.ycombinator.com/item?id=48258915

esafak 2 days ago [-]

You raise a good point. I think a good UX would be to give the user more control over fidelity; locally, and globally.

dj_axl 2 days ago [-]

Any denoising?

https://github.com/Twinklebear/oidn-rs

rmi0 1 days ago [-]

There are some noise-handling pieces, but no public denoising API. E.g.: Wiener/unsupervised Wiener configs, NSR estimation, regularization, and simulation helpers for Gaussian/Poisson/readout noise. The crate is focused on deconvolution.

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