Point spread function estimation with computed wavefronts for deconvolution of hyperspectral imaging data

authored by: Miroslav Zabic, Michel Reifenrath, Charlie Wegner, Hans Bethge, Timm Landes, Sophia Rudorf, Dag Heinemann
Abstract: Hyperspectral imaging (HSI) systems acquire images with spectral information over a wide range of wavelengths but are often affected by chromatic and other optical aberrations that degrade image quality. Deconvolution algorithms can improve the spatial resolution of HSI systems, yet retrieving the point spread function (PSF) is a crucial and challenging step. To address this challenge, we have developed a method for PSF estimation in HSI systems based on computed wavefronts. The proposed technique optimizes an image quality metric by modifying the shape of a computed wavefront using Zernike polynomials and subsequently calculating the corresponding PSFs for input into a deconvolution algorithm. This enables noise-free PSF estimation for the deconvolution of HSI data, leading to significantly improved spatial resolution and spatial co-registration of spectral channels over the entire wavelength range.
Organisation(s): Hannover Centre for Optical Technologies (HOT)
Institute of Horticultural Production Systems
PhoenixD: Photonics, Optics, and Engineering - Innovation Across Disciplines
Institute of Cell Biology and Biophysics
External Organisation(s): Haip Solutions GmbH
Type: Article
Journal: Scientific reports
Volume: 15
ISSN: 2045-2322
Publication date: 03.01.2025
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General
Electronic version(s): https://doi.org/10.1038/s41598-024-84790-6 (Access: Open)

BibTeX

@article{7d14f60d74114b62ab6c9c4a7f7054e6,
title = "Point spread function estimation with computed wavefronts for deconvolution of hyperspectral imaging data",
abstract = "Hyperspectral imaging (HSI) systems acquire images with spectral information over a wide range of wavelengths but are often affected by chromatic and other optical aberrations that degrade image quality. Deconvolution algorithms can improve the spatial resolution of HSI systems, yet retrieving the point spread function (PSF) is a crucial and challenging step. To address this challenge, we have developed a method for PSF estimation in HSI systems based on computed wavefronts. The proposed technique optimizes an image quality metric by modifying the shape of a computed wavefront using Zernike polynomials and subsequently calculating the corresponding PSFs for input into a deconvolution algorithm. This enables noise-free PSF estimation for the deconvolution of HSI data, leading to significantly improved spatial resolution and spatial co-registration of spectral channels over the entire wavelength range.",
author = "Miroslav Zabic and Michel Reifenrath and Charlie Wegner and Hans Bethge and Timm Landes and Sophia Rudorf and Dag Heinemann",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",
year = "2025",
month = jan,
day = "3",
doi = "10.1038/s41598-024-84790-6",
language = "English",
volume = "15",
journal = "Scientific reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",
}