ArticleLight, science & applications2016
Point spread function estimation from projected speckle illumination.
Article in Light, science & applications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- High-resolution quantitative phase imaging via vortex beam speckle illumination.Biomedical optics express · 2025Article
- Randomness assisted in-line holography with deep learning.Scientific reports · 2023Article
- Intensity correlation scan (IC-scan) technique to characterize the optical nonlinearities of scattering media.Scientific reports · 2023Article
- Fluorescent nanodiamonds for characterization of nonlinear microscopy systems.Photonics research · 2021Article
- All-fiber few-mode optical coherence tomography using a modally-specific photonic lantern.Biomedical optics express · 2021Article
- Comparison of tissue dispersion measurement techniques based on optical coherence tomography.Journal of biomedical optics · 2019Article
- Using speckle to measure tissue dispersion in optical coherence tomography.Biomedical optics express · 2017Article
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Authors and funding
3 authors.
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Abstract
The resolution of an imaging apparatus is ideally limited by the diffraction properties of the light passing through the system aperture, but in many practical cases, inhomogeneities in the light propagating medium or imperfections in the optics degrade the image resolution. Here we introduce a powerful and practical new approach for estimating the point spread function (PSF) of an imaging system on the basis of PSF Estimation from Projected Speckle Illumination (PEPSI). PEPSI uses the fact that the speckles' phase randomness cancels the effects of the aberrations in the illumination path, thereby providing an objective pattern for measuring the deformation of the imaging path. Using this approach, both wide-field-of-view and local-PSF estimation can be obtained by calibration-free, single-speckle-pattern projection. Finally, we demonstrate the feasibility of using PEPSI estimates for resolution improvement in iterative maximum likelihood deconvolution.
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