Deconvolution – a Rust image deconvolution and restoration crate

Name: Deconvolution – a Rust image deconvolution and restoration crate
Availability: InStock
Author: rmi0

by rmi0·Jun 15, 2026·33 points·5 comments

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AI Analysis

●●SolidBig BrainNiche Gem

28 deconvolution algorithms in Rust with proper PSF modeling and ndarray support.

Strengths

•Comprehensive algorithm coverage from practical Wiener filters to research-grade MLE restoration.
•Proper scientific imaging support with PSF/OTF conversion and microscopy-specific models.
•Clean Rust API using image::DynamicImage with optional rayon parallelization.

Weaknesses

•Niche audience limits adoption—most developers never need image deconvolution.
•WIP status with only 60 commits suggests early-stage maturity.

Post Description

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:)