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Super-resolution imaging has revolutionized the study of systems ranging from molecular structures to distant galaxies. However, existing super-resolution methods require extensive calibration and retraining for each imaging setup, limiting…

Optics · Physics 2026-03-24 Dominik Vašinka , Filip Juráň , Jaromír Běhal , Miroslav Ježek

No imaging apparatus can produce perfect images: spatial resolution is limited by the Rayleigh diffraction bound that is a consequence of the imager's finite spatial extent. We show some N-photon strategies that permit resolution of details…

Quantum Physics · Physics 2009-02-25 Vittorio Giovannetti , Seth Lloyd , Lorenzo Maccone , Jeffrey H. Shapiro

Super-resolution microscopy overcomes the diffraction limit of conventional light microscopy in spatial resolution. By providing novel spatial or spatio-temporal information on biological processes at nanometer resolution with molecular…

Biological Physics · Physics 2021-11-10 Tianjie Yang , Yaoru Luo , Wei Ji , Ge Yang

Quantum phenomena such as entanglement can improve fundamental limits on the sensitivity of a measurement probe. In optical interferometry, a probe consisting of $N$ entangled photons provides up to a $\sqrt{N}$ enhancement in phase…

We show star images obtained with a miniature ``densified pupil imaging interferometer'' also called a hyper-telescope. The formation of such images violates a ``golden rule of imaging interferometers'' which appeared to forbid the use of…

Astrophysics · Physics 2009-10-31 E. Pedretti , A. Labeyrie , L. Arnold , N. Thureau , O. Lardiere , A. Boccaletti , P. Riaud

We develop an interpolation-based modeling framework for parameter-dependent partial differential equations arising in control, inverse problems, and uncertainty quantification. The solution is discretized in the physical domain using…

Numerical Analysis · Mathematics 2026-04-20 Erik Burman , Mats G. Larson , Karl Larsson , Jonatan Vallin

Image deconvolution is the process of recovering convolutional degraded images, which is always a hard inverse problem because of its mathematically ill-posed property. On the success of the recently proposed deep image prior (DIP), we…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Zhunxuan Wang , Zipei Wang , Qiqi Li , Hakan Bilen

The next generation of Extremely Large Telescopes (ELT), with diameters up to 39 meters, will start opera- tion in the next decade and promises new challenges in the development of instruments. The growing field of astrophotonics (the use…

Instrumentation and Methods for Astrophysics · Physics 2014-08-07 N. Blind , E. Le Coarer , P. Kern , J. Bland-Hawthorn

Face super-resolution aims to reconstruct a high-resolution face image from a low-resolution face image. Previous methods typically employ an encoder-decoder structure to extract facial structural features, where the direct downsampling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Wenjie Li , Heng Guo , Xuannan Liu , Kongming Liang , Jiani Hu , Zhanyu Ma , Jun Guo

Extra-large apertures, high carrier frequencies, and integrated sensing and communications (ISAC) are pushing array processing into the Fresnel region, where spherical wavefronts induce a range-dependent phase across the aperture. This…

Signal Processing · Electrical Eng. & Systems 2026-02-17 Sajad Daei , Gábor Fodor , Mikael Skoglund

This paper tackles the challenging problem of hyperspectral (HS) image denoising. Unlike existing deep learning-based methods usually adopting complicated network architectures or empirically stacking off-the-shelf modules to pursue…

Image and Video Processing · Electrical Eng. & Systems 2022-07-12 Jinhui Hou , Zhiyu Zhu , Hui Liu , Junhui Hou

Microarcsecond resolutions afforded by an optical-NIR array with kilometer-baselines would enable breakthrough science. However significant technology barriers exist in transporting weakly coherent photon states over these distances:…

Fully connected layer is an essential component of Convolutional Neural Networks (CNNs), which demonstrates its efficiency in computer vision tasks. The CNN process usually starts with convolution and pooling layers that first break down…

Computer Vision and Pattern Recognition · Computer Science 2020-09-24 M. Amine Mahmoudi , Aladine Chetouani , Fatma Boufera , Hedi Tabia

Deconvolution is essential for radio interferometric imaging to produce scientific quality data because of finite sampling in the Fourier plane. Most deconvolution algorithms are based on CLEAN which uses a grid of image pixels, or clean…

Instrumentation and Methods for Astrophysics · Physics 2016-11-18 Sarod Yatawatta

In the realm of aerial image analysis, object detection plays a pivotal role, with significant implications for areas such as remote sensing, urban planning, and disaster management. This study addresses the inherent challenges in this…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Ahmed Sharshar , Aleksandr Matsun

In recent years, computational Time-of-Flight (ToF) imaging has emerged as an exciting and a novel imaging modality that offers new and powerful interpretations of natural scenes, with applications extending to 3D, light-in-flight, and…

Image and Video Processing · Electrical Eng. & Systems 2024-11-05 Ruiming Guo , Ayush Bhandari

A kernel based procedure for correcting experimental data for distortions due to the finite resolution and limited detector acceptance is presented. The unfolding problem is known to be an ill-posed problem that can not be solved without…

Data Analysis, Statistics and Probability · Physics 2012-09-19 N. D. Gagunashvili , M. Schmelling

Modern x-ray light sources promise access to structure and dynamics of matter in largely unexplored spectral regions. However, the desired information is encoded in the light intensity and phase, whereas detectors register only the…

Quantum Physics · Physics 2015-06-10 K. P. Heeg , C. Ott , D. Schumacher , H. -C. Wille , R. Röhlsberger , T. Pfeifer , J. Evers

The classically defined minimum uncertainty of the optical phase is known as the standard quantum limit or shot-noise limit (SNL) originating in the uncertainty principle of quantum mechanics. Based on SNL, the phase sensitivity is…

Quantum Physics · Physics 2024-05-29 Byoung S. Ham

The last decade has shown the great potential that X-ray Free Electron Lasers (FEL) have to study High Energy Density (HED) physics. Experiments at FELs have made significant breakthroughs in Shock Physics and Dynamic Diffraction, Dense…