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Improving axial resolution is crucial for three-dimensional optical imaging systems. Here we present a scheme of axial superresolution for two incoherent point sources based on spatial mode demultiplexing. A radial mode sorter is used to…

We present a semi-blind, spatially-variant deconvolution technique aimed at optical microscopy that combines a local estimation step of the point spread function (PSF) and deconvolution using a spatially variant, regularized Richardson-Lucy…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Adrian Shajkofci , Michael Liebling

Richardson-Lucy deconvolution is widely used to restore images from degradation caused by the broadening effects of a point spread function and corruption by photon shot noise, in order to recover an underlying object. In practice, this is…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Zachary H. Hendrix , Peter T. Brown , Tim Flanagan , Douglas P. Shepherd , Ayush Saurabh , Steve Pressé

Super-resolution microscopes (such as STED) illuminate samples with a tiny spot, and achieve very high resolution. But structures smaller than the spot cannot be resolved in this way. Therefore, we propose a technique to solve this problem.…

Image and Video Processing · Electrical Eng. & Systems 2019-11-20 Yaohua Xie

Optical microscopy is an essential tool in biology and medicine. Imaging thin, yet non-flat objects in a single shot (without relying on more sophisticated sectioning setups) remains challenging as the shallow depth of field that comes with…

Image and Video Processing · Electrical Eng. & Systems 2020-10-14 Adrian Shajkofci , Michael Liebling

Super-resolution techniques overcome the diffraction-limit and get very high resolutions. A category of these techniques, e.g., STED achieves this by creating an illumination spot smaller than the Airy Disk. As a result, points are…

Image and Video Processing · Electrical Eng. & Systems 2019-11-20 Yaohua Xie

We propose an image resolution improvement method for optical coherence tomography (OCT) based on sparse continuous deconvolution. Traditional deconvolution techniques such as Lucy-Richardson deconvolution suffers from the artifact…

Biological Physics · Physics 2023-04-11 Zhengyu Qiao , Yong Huang , Qun Hao

The most ubiquitous form of computational aberration correction for microscopy is deconvolution. However, deconvolution relies on the assumption that the point spread function is the same across the entire field-of-view. This assumption is…

Image and Video Processing · Electrical Eng. & Systems 2025-04-30 Amit Kohli , Anastasios N. Angelopoulos , David McAllister , Esther Whang , Sixian You , Kyrollos Yanny , Federico M. Gasparoli , Bo-Jui Chang , Reto Fiolka , Laura Waller

Dusty star-forming galaxies (DSFGs) dominate the far-infrared and sub-millimetre number counts, but single-dish surveys suffer from poor angular resolution, complicating mult-wavelength counterpart identification. Prior-driven deblending…

Lensless microscopy with coherent or partially coherent light sources is a well known imaging technique, commonly referred as digital in-line holographic microscopy. In the established methods, both the spatial and temporal coherence of…

Optics · Physics 2020-11-04 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta

We consider the problem of estimating the spatial separation between two mutually incoherent point light sources using the super-resolution imaging technique based on spatial mode demultiplexing with noisy detectors. We show that in the…

Quantum Physics · Physics 2020-03-26 Yink Loong Len , Chandan Datta , Michał Parniak , Konrad Banaszek

Deconvolution is the most widely used aberration correction technique in microscopy, however most techniques assume that the aberrations are the same for each point in the image, which is rarely true. Methods for tracking spatially varying…

Optics · Physics 2025-12-02 Jakub Czuchnowski , Chuan Li , Hongli Ni , Brandon Weissbourd , Jerome Mertz

In this work we present a new algorithm for data deconvolution that allows the retrieval of the target function with super-resolution with a simple approach that after a precis e measurement of the instrument response function (IRF), the…

Computer Vision and Pattern Recognition · Computer Science 2018-12-07 Sandra Martínez , Oscar E. Martínez

We present a physics-informed deep learning framework to address common limitations in Confocal Laser Scanning Microscopy (CLSM), such as diffraction limited resolution, noise, and undersampling due to low laser power conditions. The…

Materials Science · Physics 2025-01-27 Zaheer Ahmad , Junaid Shabeer , Usman Saleem , Tahir Qadeer , Abdul Sami , Zahira El Khalidi , Saad Mehmood

Confocal laser scanning microscopy (CLSM) stands out as one of the most widely used microscopy techniques, thanks to its three-dimensional imaging capability and its sub-diffraction spatial resolution, achieved through the closure of a…

Super-resolution structured illumination microscopy (SR-SIM) is a widely used technique for enhancing the resolution of fluorescence imaging beyond the diffraction limit. Most existing SR-SIM methods rely on Moir\'e effect-based physical…

Optics · Physics 2025-02-27 Junzheng Peng , Jiahao Xian , Xi Lin , Manhong Yao , Shiping Li , Jingang Zhong

A method for spatial deconvolution of spectra is presented. It follows the same fundamental principles as the ``MCS image deconvolution algorithm'' (Magain, Courbin, Sohy, 1998) and uses information contained in the spectrum of a reference…

Astrophysics · Physics 2009-10-31 F. Courbin , P. Magain , M. Kirkove , S. Sohy

We demonstrate spectroscopy of incoherent light with sub-diffraction resolution. In a proof-of-principle experiment we analyze the spectrum of a pair of incoherent point-like sources whose separation is below the diffraction limit. The two…

The Richardson-Lucy method is the most popular deconvolution method in astronomy because it preserves the number of counts and the non-negativity of the original object. Regularization is, in general, obtained by an early stopping of…

Instrumentation and Methods for Astrophysics · Physics 2012-10-10 M. Prato , R. Cavicchioli , L. Zanni , P. Boccacci , M. Bertero

Deep learning-based hyperspectral image super-resolution (SR) methods have achieved great success recently. However, most existing models can not effectively explore spatial information and spectral information between bands simultaneously,…

Computer Vision and Pattern Recognition · Computer Science 2020-01-15 Qi Wang , Qiang Li , Xuelong Li
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