Original	Deconvolved

Before (left) is the motion-blurred sample; after (right) is restored using wiener_with.

Rust image deconvolution and restoration library.

Recovering images from blur depends on a point-spread function, stable frequency-domain utilities, and careful regularization. deconvolution provides known-PSF restoration, blind workflows, PSF/OTF conversion, preprocessing helpers, simulation fixtures, and ndarray APIs.

Overview

• Image API: Top-level functions use image::DynamicImage and return images ready to save.
• Known PSF methods: Inverse filters, Wiener, Richardson-Lucy, constrained, proximal, Krylov, and MLE-style restoration.
• Blind methods: Blind Richardson-Lucy, blind maximum likelihood, and parametric PSF estimation.
• PSF and OTF types: Kernel2D, Kernel3D, Transfer2D, Transfer3D, and Blur2D/Blur3D.
• PSF tools: Gaussian, motion, defocus, microscopy models, support utilities, and PSF/OTF conversion.
• Preprocessing: Edge tapering, apodization, range normalization, and NSR estimation.
• Simulation: Deterministic blur, noise, and synthetic fixture generation.
• ndarray support: 2D image arrays and 3D volume workflows.
• Feature flags: rayon by default; optional f16 support.

Installation

[dependencies]
deconvolution = "0.2.0"

Image loading: Add image when your application opens or saves image files.

Serial build: Disable default features to turn off rayon.

[dependencies]
deconvolution = { version = "0.2.0", default-features = false }

Quick Start

use deconvolution::psf::basic::gaussian2d;
use deconvolution::spectral::{wiener_with, Wiener};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let input = image::open("before_deconvolution.png")?;
    let psf = gaussian2d((15, 15), 2.15)?;

    let restored = wiener_with(&input, &psf, &Wiener::new().nsr(2.5e-4))?;
    restored.save("after_deconvolution.png")?;

    Ok(())
}

Image API

Supported DynamicImage variants:

• ImageLuma8
• ImageLumaA8
• ImageRgb8
• ImageRgba8
• ImageLuma16
• ImageLumaA16
• ImageRgb16
• ImageRgba16
• ImageRgb32F
• ImageRgba32F

Configuration enums are shared across algorithm families:

• Boundary: Zero, Replicate, Reflect, Symmetric, Periodic
• Padding: None, Same, Minimal, NextFastLen, Explicit2, Explicit3
• ChannelMode: Independent, LumaOnly, IgnoreAlpha, PremultipliedAlpha
• RangePolicy: PreserveInput, Clamp01, ClampNegPos1, Unbounded

Use ChannelMode::Independent for per-channel color restoration, ChannelMode::LumaOnly when the blur should primarily affect luminance, and RangePolicy::PreserveInput when working in normal image sample ranges.

PSF and OTF API

Basic PSF generators:

• delta2d, delta3d
• gaussian2d, gaussian3d
• motion_linear
• disk, pillbox, defocus
• box2d, box3d
• oriented_gaussian

Blind initialization helpers:

• psf::init::uniform
• psf::init::gaussian_guess
• psf::init::motion_guess
• psf::init::from_support

Support utilities:

• normalize, normalize_3d
• center, center_3d
• pad_to, pad_to_3d
• crop_to, crop_to_3d
• flip, flip_3d
• validate, validate_3d
• support_mask, support_mask_3d

Transfer conversion utilities:

• otf::convert::psf2otf
• otf::convert::psf2otf_3d
• otf::convert::otf2psf
• otf::convert::otf2psf_3d

Optical and microscopy models:

• BornWolfParams / born_wolf
• GibsonLanniParams / gibson_lanni
• VariableRiGibsonLanniParams / variable_ri_gibson_lanni
• RichardsWolfParams / richards_wolf
• lorentz2d
• astigmatic
• double_helix
• otf::spectra::koehler_otf
• otf::spectra::defocus_otf

Known PSF Methods

Spectral and inverse filters

Frequency-domain restoration.

• naive_inverse_filter
• inverse_filter
• truncated_inverse_filter
• regularized_inverse_filter
• tikhonov_inverse_filter
• wiener
• unsupervised_wiener

Configuration types:

• InverseFilter
• RegularizedInverseFilter
• TikhonovInverseFilter
• Wiener
• UnsupervisedWiener

Custom configs: Use _with variants.

Richardson-Lucy and regularized RL

Poisson-style multiplicative restoration.

• richardson_lucy
• damped_richardson_lucy
• richardson_lucy_tv

Configuration types:

• RichardsonLucy
• RichardsonLucyTv

Iterative least-squares methods

Residual-update restoration.

• landweber
• van_cittert
• tikhonov_miller
• ictm

Configuration types:

• Landweber
• VanCittert
• TikhonovMiller
• Ictm

Constrained solvers

Bound-aware restoration.

• nnls
• bvls

Configuration types:

• Nnls
• Bvls

Sparse and proximal methods

Proximal-gradient restoration.

• ista
• fista

Configuration and model types:

• Ista
• Fista
• SparseBasis

Krylov and advanced iterative methods

Scientific imaging solvers.

• mrnsd
• cgls
• wpl
• hybr

Configuration types:

• Mrnsd
• Cgls
• Wpl
• Hybr

Maximum-likelihood family

Microscopy-oriented MLE-style restoration.

• cmle
• gmle
• qmle

Configuration types:

• Cmle
• Gmle
• Qmle

Blind Deconvolution

Blind workflows estimate both the restored image and the PSF. Image-facing blind workflows support Gray and GrayAlpha DynamicImage variants for u8 and u16 samples.

• blind::richardson_lucy
• blind::maximum_likelihood
• blind::parametric

blind::maximum_likelihood shares the same Poisson EM restoration core as blind Richardson-Lucy.

Configuration and output types:

• BlindRichardsonLucy
• BlindMaximumLikelihood
• BlindParametric
• BlindOutput<I>
• BlindReport
• ParametricPsf
• PsfConstraint

PSF constraints:

• Nonnegative
• NormalizeSum
• SupportMask(...)

Parametric PSF families:

• Gaussian { sigma }
• MotionLinear { length, angle_deg }
• Defocus { radius }
• OrientedGaussian { sigma_major, sigma_minor, angle_deg }

ndarray Workflows

The public nd module exposes array-first workflows for users who already work in ndarray or need 3D volumes. Enable the optional f16 feature to pass half::f16 arrays into the 2D ndarray API while keeping computation in f32.

2D known-PSF methods in nd::known_psf:

• wiener, unsupervised_wiener
• richardson_lucy, richardson_lucy_tv
• landweber, van_cittert, tikhonov_miller, ictm
• nnls, bvls
• ista, fista
• mrnsd, cgls, wpl, hybr

Blind methods in nd::blind:

• richardson_lucy
• maximum_likelihood

3D and microscopy methods in nd::microscopy:

• wiener
• richardson_lucy
• richardson_lucy_tv
• cmle
• gmle
• qmle

Preprocessing

Preprocessing utilities help reduce ringing and prepare numerical inputs.

• preprocess::apodize
• preprocess::apodize::window_edges
• preprocess::edgetaper
• preprocess::estimate_nsr
• preprocess::normalize_range

Use edgetaper or apodization before frequency-domain deconvolution when strong edge discontinuities create ringing artifacts.

Simulation and Fixtures

Deterministic: Same input and seed produce the same simulated output.

Fixtures: Synthetic images and volumes for tests, examples, and benchmarks.

Blur and degradation:

• simulate::blur::blur
• simulate::blur::blur_otf
• simulate::blur::blur_3d
• simulate::blur::blur_otf_3d
• simulate::blur::degrade

Noise models:

• simulate::noise::add_gaussian_noise
• simulate::noise::add_poisson_noise
• simulate::noise::add_readout_noise

Synthetic fixtures:

• simulate::phantom::checkerboard_2d
• simulate::phantom::gaussian_blob_2d
• simulate::phantom::rgb_edges_2d
• simulate::phantom::phantom_3d

Optional rayon Integration

rayon is enabled by default. The optional f16 feature adds half::f16 input/output support for the 2D ndarray API; computation remains in f32.

[features]
default = ["rayon"]
rayon = ["dep:rayon", "ndarray/rayon", "image/rayon"]
f16 = ["dep:half"]

Disable default features for serial builds:

cargo test --no-default-features

Example Programs

Image-facing workflows:

cargo run --example wiener -- input.png output.png
cargo run --example richardson_lucy
cargo run --example blind_motion
cargo run --example edgetaper
cargo run --example custom_regularizer

Volume workflow:

cargo run --example microscopy_volume

Benchmarks and Development

Benchmarks: Criterion benchmark families.

• spectral
• rl
• blind
• volume

cargo bench --no-run
cargo bench --bench spectral
cargo bench --bench rl
cargo bench --bench blind
cargo bench --bench volume

Checks:

cargo fmt --all -- --check
cargo clippy --workspace --all-targets --all-features -- -D warnings
cargo check --all-features
cargo test --workspace --all-targets --all-features
cargo doc --workspace --no-deps --all-features

Limitations and Scope

• Known-PSF image-facing algorithms support u8/u16 Gray, GrayAlpha, Rgb, and Rgba DynamicImage variants, plus 32-bit float Rgb and Rgba images.
• Blind image-facing algorithms support u8/u16 Gray and GrayAlpha DynamicImage variants.

License

deconvolution is licensed under the MIT License, copyright (c) 2026 pbkx.