Work

Reducing ringing artifacts in Wiener deconvolution using implicit physical priors

Year: 2026

Type: article

Abstract: With advances in high-speed imaging there is a growing need for robust high-speed deconvolution algorithms. Wiener deconvolution remains one of the fastest and simplest algorithms available, however it suffers from ringing artifacts that can limit its applicability. In this work, we develop two complementary, computationally efficient heuristic methods to suppress these ringing artifacts by using physical non-negativity and sparsity priors.

Source: Optics Letters

DOI: 10.1364/ol.619118

Authors: Jakub Czuchnowski, Jerome Mertz

Language: English

Topic: Image and Signal Denoising Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute of Neurological Disorders and Stroke

Awards: Nanosystems Engineering Research Center for Directed Multiscale Assembly of Cellular Metamaterials with Nanoscale Precision: CELL-MET, G5043199207, Multi-Layer Neuronal Imaging with Reverberation Multiphoton Microscopy, Robust high-throughput superresolution imaging with speckle illumination

OpenAlex ID: W7214120011

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