Show HN: Deconvolution – a Rust image deconvolution and restoration crate
25 points
by rmi0
2 days ago
| 2 comments
| github.com
| HN
I've been working on deconvolution, a comprehensive Rust image deconvolution and restoration library. Deconvolution implements 28 different image deconvolution/restoration methods which range from practical blur removal techniques to research-grade scientific imaging algorithms.

Features:

- Top-level functions use image::DynamicImage and return images

- Inverse filters, Wiener, Richardson-Lucy, constrained, proximal, Krylov, MLE restoration

- Blind Richardson-Lucy, blind maximum likelihood, parametric PSF estimation

- Kernel2D, Kernel3D, Transfer2D, Transfer3D, Blur2D/Blur3D

- Gaussian, motion, defocus, microscopy models, support utilities, PSF/OTF conversion

- Edge tapering, apodization, range normalization, NSR estimation

- Deterministic blur, noise, synthetic fixture generation

- ndarray support for 2D image arrays and 3D volume

this project is a WIP, of course:)

dj_axl
30 minutes ago
[-]
reply
esafak
1 hour 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.
reply
srean
40 minutes ago
[-]
reply
esafak
30 minutes ago
[-]
You raise a good point. I think a good UX would be to give the user more control over fidelity; locally, and globally.
reply