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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

Deconvolution is the most commonly used image processing method to remove the blur caused by the point-spread-function (PSF) in optical imaging systems. While this method has been successful in deblurring, it suffers from several…

Image and Video Processing · Electrical Eng. & Systems 2019-10-10 Huangxuan Zhao , Ziwen Ke , Ningbo Chen , Ke Li , Lidai Wang , Xiaojing Gong , Wei Zheng , Liang Song , Zhicheng Liu , Dong Liang , Chengbo Liu

Rotating synthetic aperture (RSA) imaging system captures images of the target scene at different rotation angles by rotating a rectangular aperture. Deblurring acquired RSA images plays a critical role in reconstructing a latent sharp…

Methodology · Statistics 2025-02-03 Dao Lin , Jian Zhang , Martin Benning

A new method for improving the resolution of astronomical images is presented. It is based on the principle that sampled data cannot be fully deconvolved without violating the sampling theorem. Thus, the sampled image should not be…

Astrophysics · Physics 2009-10-30 P. Magain , F. Courbin , S. Sohy

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to…

Image and Video Processing · Electrical Eng. & Systems 2019-07-22 Mahdi S. Hosseini , Konstantinos N. Plataniotis

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

Optic deconvolution in light microscopy (LM) refers to recovering the object details from images, revealing the ground truth of samples. Traditional explicit methods in LM rely on the point spread function (PSF) during image acquisition.…

Quantitative Methods · Quantitative Biology 2026-03-24 Rui Li , Mikhail Kudryashev , Artur Yakimovich

Reproducing an all-in-focus image from an image with defocus regions is of practical value in many applications, eg, digital photography, and robotics. Using the output of some existing defocus map estimator, existing approaches first…

Computer Vision and Pattern Recognition · Computer Science 2018-08-29 Guodong Xu , Chaoqiang Liu , Hui Ji

The miniaturization of optics through the use of two-dimensional metalenses has enabled novel applications in imaging. To date, single-lens imaging remains the most common configuration, in part due to the limited focusing efficiency of…

The interest of compressive sampling in ultrasound imaging has been recently extensively evaluated by several research teams. Following the different application setups, it has been shown that the RF data may be reconstructed from a small…

Computer Vision and Pattern Recognition · Computer Science 2015-12-07 Zhouye Chen , Adrian Basarab , Denis Kouamé

A point-spread function describes the optics of an imaging system and can be used to correct collected images for instrumental effects. The state of the art for deconvolving images with the point-spread function is the Richardson-Lucy…

Instrumentation and Methods for Astrophysics · Physics 2024-05-07 Stefan Johann Hofmeister

Non-blind rotary motion deblurring (RMD) aims to recover the latent clear image from a rotary motion blurred (RMB) image. The rotation center is a crucial input parameter in non-blind RMD methods. Existing methods directly estimate the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jinhui Qin , Yong Ma , Jun Huang , Fan Fan , You Du

The alternating direction method of multipliers (ADMM) has recently sparked interest as a flexible and efficient optimization tool for imaging inverse problems, namely deconvolution and reconstruction under non-smooth convex regularization.…

Optimization and Control · Mathematics 2015-06-11 Mariana S. C. Almeida , Mário A. T. Figueiredo

This paper demonstrates a practical method that can correct spatial varying blur from a set of images of the same object. The algorithm jointly estimates the object and local point spread functions~(PSF). The method prioritizes sections…

Image and Video Processing · Electrical Eng. & Systems 2020-11-04 Wouter van de Ketterij , Oleg Soloviev , Michel Verhaegen

In multi-photon microscopy (MPM), a recent in-vivo fluorescence microscopy system, the task of image restoration can be decomposed into two interlinked inverse problems: firstly, the characterization of the Point Spread Function (PSF) and…

Image and Video Processing · Electrical Eng. & Systems 2024-11-08 Julien Ajdenbaum , Emilie Chouzenoux , Claire Lefort , Ségolène Martin , Jean-Christophe Pesquet

Exploring motion information is important for the motion deblurring task. Recent the window-based transformer approaches have achieved decent performance in image deblurring. Note that the motion causing blurry results is usually composed…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Duosheng Chen , Shihao Zhou , Jinshan Pan , Jinglei Shi , Lishen Qu , Jufeng Yang

An optical imaging system forms an object image by recollecting light scattered by the object. However, intact optical information of the object delivered through the imaging system is deteriorated by imperfect optical elements and unwanted…

Optics · Physics 2017-03-28 SangYun Lee , Kyeoreh Lee , Seungwoo Shin , YongKeun Park

Images of near-field SAR contains spatial-variant sidelobes and clutter, subduing the image quality. Current image restoration methods are only suitable for small observation angle, due to their assumption of 2D spatial-invariant…

Signal Processing · Electrical Eng. & Systems 2022-10-06 Wensi Zhang , Xiaoling Zhang , Xu Zhan , Yuetonghui Xu , Jun Shi , Shunjun Wei

Methods of three-dimensional deconvolution (3DD) or volumetric deconvolution of optical complex-valued wavefronts diffracted by 3D samples with the 3D point spread function are presented. Particularly, the quantitative correctness of the…

Optics · Physics 2022-01-11 Tatiana Latychevskaia

Using diffusion models to solve inverse problems is a growing field of research. Current methods assume the degradation to be known and provide impressive results in terms of restoration quality and diversity. In this work, we leverage the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Charles Laroche , Andrés Almansa , Eva Coupete
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