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We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty. The problem is formulated in the…

Systems and Control · Electrical Eng. & Systems 2020-09-07 Vedang M. Deshpande , Raktim Bhattacharya

The advent of large aperture arrays, such as the ones currently under construction for the SKA project, allows for observing the Universe in the radio-spectrum at unprecedented resolution and sensitivity. To process the enormous amounts of…

Instrumentation and Methods for Astrophysics · Physics 2025-07-31 S. Wang , S. Mignot , S. Prunet , L. Di Mascolo , M. Spinelli , A. Ferrari

In this paper we report the first airborne experiments of sparse microwave imaging, conducted in September 2013 and May 2014, using our prototype sparse microwave imaging radar system. This is the first reported imaging radar system and…

Signal Processing · Electrical Eng. & Systems 2021-10-22 Zhe Zhang , Bingchen Zhang , Chenglong Jiang , Xingdong Liang , Longyong Chen , Wen Hong , Yirong Wu

The problem of learning a sparse model is conceptually interpreted as the process of identifying active features/samples and then optimizing the model over them. Recently introduced safe screening allows us to identify a part of non-active…

Machine Learning · Statistics 2016-02-09 Atsushi Shibagaki , Masayuki Karasuyama , Kohei Hatano , Ichiro Takeuchi

The sparse representation of signals defined on Euclidean domains has been successfully applied in signal processing. Bringing the power of sparse representations to non-regular domains is still a challenge, but promising approaches have…

Computational Geometry · Computer Science 2020-11-26 Lizeth J. Fuentes Perez , Luciano A. Romero Calla , Anselmo A. Montenegro , Claudio Mura , Renato Pajarola

Recently, sparsity-based algorithms are proposed for super-resolution spectrum estimation. However, to achieve adequately high resolution in real-world signal analysis, the dictionary atoms have to be close to each other in frequency,…

Machine Learning · Statistics 2015-06-05 Yiyuan She , Huanghuang Li , Jiangping Wang , Dapeng Wu

An image super-resolution method from multiple observation of low-resolution images is proposed. The method is based on sub-pixel accuracy block matching for estimating relative displacements of observed images, and sparse signal…

Computer Vision and Pattern Recognition · Computer Science 2014-02-18 Toshiyuki Kato , Hideitsu Hino , Noboru Murata

We describe a practical implementation of the anamorphically curved detector concept. In order to demonstrate its advantages, a telescope lab prototype was developed, built, and tested. It is based on a 4-mirror all-spherical unobscured…

Instrumentation and Methods for Astrophysics · Physics 2025-03-13 Eduard Muslimov , Simona Lombardo , Thibault Behaghel , Jiawei Liu , Emmanuel Hugot

Speckle photography can be used to monitor deformations of solid surfaces. The measuring characteristics, such as range or lateral resolution depend heavily on the optical recording and illumination set-up. This paper shows how, by the…

Optics · Physics 2014-01-30 Jose M. Diazdelacruz

The next generation of large telescopes for direct imaging of exoplanets will require segmented primary mirrors. Over both long and short timescales, these telescopes experience segment misalignments which degrade the final science image.…

The evolution of the scanning modules for scanning transmission electron microscopes (STEM) has realized the possibility to generate arbitrary scan pathways, an approach currently explored to improve acquisition speed and to reduce electron…

We consider the sensing of scalar valued fields with specific spatial dependence using a network of sensors, e.g. multiple atoms located at different positions within a trap. We show how to harness the spatial correlations to sense only a…

Quantum Physics · Physics 2022-08-03 Arne Hamann , Pavel Sekatski , Wolfgang Dür

Realizing continuous sweeping of perfect anomalous reflection in a wide angular range has become a technical challenge. This challenge cannot be overcome by the conventional aperiodic reflectarrays and periodic metasurfaces or metagratings.…

Capturing high resolution imagery of the Earth's surface often calls for a telescope of considerable size, even from Low Earth Orbits (LEO). A large aperture often requires large and expensive platforms. For instance, achieving a resolution…

Instrumentation and Methods for Astrophysics · Physics 2024-03-28 Maxime Dumont , Carlos M. Correia , Jean-François Sauvage , Noah Schwartz , Morgan Gray , Jaime Cardoso

Existing unsupervised image alignment methods exhibit limited accuracy and high computational complexity. To address these challenges, we propose a dense cross-scale image alignment model. It takes into account the correlations between…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Jinkun You , Jiaxue Li , Jie Zhang , Yicong Zhou

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

Signal processing is rich in inherently continuous and often nonlinear applications, such as spectral estimation, optical imaging, and super-resolution microscopy, in which sparsity plays a key role in obtaining state-of-the-art results.…

Machine Learning · Computer Science 2020-03-23 Luiz F. O. Chamon , Yonina C. Eldar , Alejandro Ribeiro

We present a proposal of a new type of telescopes using a rotating parabolic strip as the primary mirror. It is the most principal modification of the design of telescopes from the times of Galileo and Newton. In order to demonstrate the…

Instrumentation and Methods for Astrophysics · Physics 2013-04-25 Goce Chadzitaskos

We solve the problem of best approximation by partial isometries of given rank to an arbitrary rectangular matrix, when the distance is measured in any unitarily invariant norm. In the case where the norm is strictly convex, we parametrize…

Functional Analysis · Mathematics 2016-11-08 Jorge Antezana , Eduardo Chiumiento

Compressed sensing is an imaging paradigm that allows one to invert an underdetermined linear system by imposing the a priori knowledge that the sought after solution is sparse (i.e., mostly zeros). Previous works have shown that if one…

Image and Video Processing · Electrical Eng. & Systems 2023-12-05 Nicholas Dwork , Erin K. Englund