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Removing the aberrations introduced by the Point Spread Function (PSF) is a fundamental aspect of astronomical image processing. The presence of noise in observed images makes deconvolution a nontrivial task that necessitates the use of…

Instrumentation and Methods for Astrophysics · Physics 2017-05-03 Samuel Farrens , Jean-Luc Starck , Fred Maurice Ngolè Mboula

Lensless cameras replace bulky optics with thin modulation masks, enabling compact imaging systems. However, existing methods rely on an idealized model that assumes a globally shift-invariant point spread function (PSF) and sufficiently…

Image and Video Processing · Electrical Eng. & Systems 2025-12-02 Yu Ren , Xiaoling Zhang , Xu Zhan , Xiangdong Ma , Yunqi Wang , Edmund Y. Lam , Tianjiao Zeng

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

Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are necessary, as in optimal photometry…

Instrumentation and Methods for Astrophysics · Physics 2021-02-03 Teresa Symons , Michael Zemcov , James Bock , Yun-Ting Cheng , Brendan Crill , Christopher Hirata , Stephanie Venuto

Deep-learning (DL)-based image deconvolution (ID) has exhibited remarkable recovery performance, surpassing traditional linear methods. However, unlike traditional ID approaches that rely on analytical properties of the point spread…

Image and Video Processing · Electrical Eng. & Systems 2025-01-28 Romario Gualdrón-Hurtado , Roman Jacome , Sergio Urrea , Henry Arguello , Luis Gonzalez

In the case of ground-based telescopes equipped with adaptive optics systems, the point spread function (PSF) is only poorly known or completely unknown. Moreover, an accurate modeling of the PSF is in general not available. Therefore in…

Numerical Analysis · Mathematics 2015-06-09 M. Prato , A. La Camera , S. Bonettini , S. Rebegoldi , M. Bertero , P. Boccacci

Many microscopy applications are limited by the total amount of usable light and are consequently challenged by the resulting levels of noise in the acquired images. This problem is often addressed via (supervised) deep learning based…

Image and Video Processing · Electrical Eng. & Systems 2020-08-20 Anna S. Goncharova , Alf Honigmann , Florian Jug , Alexander Krull

One of the major limitations of adaptive optics (AO) corrected image post-processing is the lack of knowledge on the system point spread function (PSF). The PSF is not always available as a direct imaging on isolated point like objects such…

Instrumentation and Methods for Astrophysics · Physics 2020-07-22 Romain Fétick , Laurent Mugnier , Thierry Fusco , Benoit Neichel

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

Simulated images are essential in algorithm development and instrument testing for optical telescopes. During real observations, images obtained by optical telescopes are affected by spatially variable point spread functions (PSFs), a…

Instrumentation and Methods for Astrophysics · Physics 2025-02-17 Zeyu Bai , Peng Jia , Jiameng Lv , Xiang Zhang , Wennan Xiang , Lin Nie

In the imaging process of an astronomical telescope, the deconvolution of its beam or Point Spread Function (PSF) is a crucial task. However, deconvolution presents a classical and challenging inverse computation problem. In scenarios where…

Instrumentation and Methods for Astrophysics · Physics 2024-03-05 Shulei Ni , Yisheng Qiu , Yunchun Chen , Zihao Song , Hao Chen , Xuejian Jiang , Huaxi Chen

We explore the impact of different telescope apertures on the image simulation and deconvolution processes within the context of a synthetic star field. Using HCIPy and Python programming, we modelled six telescope apertures namely…

Instrumentation and Methods for Astrophysics · Physics 2024-02-09 Jyotika Roychowdhury , Kevin Derby , Daewook Kim

We report a point spread function (PSF) and deconvolution procedure to remove stray light from the Helioseismic and Magnetic Imager (HMI) data. Pre-launch calibration observations, post-launch Venus transit and lunar transit data were used…

Solar and Stellar Astrophysics · Physics 2025-11-18 A. A. Norton , T. L. Duvall, , J. Schou , R. S. Bogart , J. Zhao , C. Rabello-Soares , P. J. Levens , J. T. Hoeksema , C. S. Baldner

This Point spread function (PSF) plays a crucial role in many computational imaging applications, such as shape from focus/defocus, depth estimation, and fluorescence microscopy. However, the mathematical model of the defocus process is…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Renzhi He , Yan Zhuang , Boya Fu , Fei Liu

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

Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the…

Computer Vision and Pattern Recognition · Computer Science 2016-01-12 Adriana Gonzalez , Véronique Delouille , Laurent Jacques

Synthetic aperture sonar (SAS) image resolution is constrained by waveform bandwidth and array geometry. Specifically, the waveform bandwidth determines a point spread function (PSF) that blurs the locations of point scatterers in the…

Computer Vision and Pattern Recognition · Computer Science 2021-12-17 Albert Reed , Thomas Blanford , Daniel C. Brown , Suren Jayasuriya

Application of deconvolution algorithms to astronomical images is often limited by variations in PSF structure over the domain of the images. One major difficulty is that Fourier methods can no longer be used for fast convolutions over the…

Astrophysics · Physics 2009-11-07 Tod R. Lauer

Ultrasound is widely used in medical diagnostics allowing for accessible and powerful imaging but suffers from resolution limitations due to diffraction and the finite aperture of the imaging system, which restricts diagnostic use. The…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Felix Duelmer , Walter Simson , Mohammad Farid Azampour , Magdalena Wysocki , Angelos Karlas , Nassir Navab

We have shown that the vector of the point spread function (PSF) lexicographical presentation belongs to the left side conjugated null space (NS) of the autoregression (AR) matrix operator on condition the AR parameters are common for…

Computer Vision and Pattern Recognition · Computer Science 2015-03-02 Yuriy A. Bunyak , Roman N. Kvetnyy , Olga Yu. Sofina