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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

Holography is a cornerstone characterisation and imaging technique that can be applied to the full electromagnetic spectrum, from X-rays to radio waves or even particles such as neutrons. The key property in all these holographic approaches…

Quantum Physics · Physics 2021-01-12 Hugo Defienne , Bienvenu Ndagano , Ashley Lyons , Daniele Faccio

Plug-and-Play (PnP) is a non-convex optimization framework that combines proximal algorithms, for example, the alternating direction method of multipliers (ADMM), with advanced denoising priors. Over the past few years, great empirical…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Kaixuan Wei , Angelica Aviles-Rivero , Jingwei Liang , Ying Fu , Hua Huang , Carola-Bibiane Schönlieb

Scene graphs have emerged as accurate descriptive priors for image generation and manipulation tasks, however, their complexity and diversity of the shapes and relations of objects in data make it challenging to incorporate them into the…

Machine Learning · Computer Science 2023-11-07 Pavel Jahoda , Azade Farshad , Yousef Yeganeh , Ehsan Adeli , Nassir Navab

The multiplexing and de-multiplexing of orbital angular momentum (OAM) beams are critical issues in optical communication. Optical diffractive neural networks have been introduced to perform classification, generation, multiplexing and…

Optics · Physics 2022-07-20 Jiaqi Zhang , Zhiyuan Ye , Jianhua Yin , Liying Lang , Shuming Jiao

Blind deconvolution is a technique to recover an original signal without knowing a convolving filter. It is naturally formulated as a minimization of a quartic objective function under some assumption. Because its differentiable part does…

Optimization and Control · Mathematics 2022-09-13 Shota Takahashi , Mirai Tanaka , Shiro Ikeda

We introduce an algorithm for the deconvolution of radio synthesis images that accounts for the non-coplanar-baseline effect, allows multiscale reconstruction onto arbitrarily positioned pixel grids, and allows the antenna elements to have…

Instrumentation and Methods for Astrophysics · Physics 2013-10-09 Stephen J. Hardy

Arbitrary manipulation of light across multiple physical dimensions is essential for harnessing its parallelism in fundamental research and advanced applications, such as optical interconnects, computing, imaging, sensing, and quantum…

We introduce a new method to propagate uncertainties in the beam shapes used to measure the cosmic microwave background to cosmological parameters determined from those measurements. The method, which we call Markov Chain Beam…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 G. Rocha , L. Pagano , K. M. Górski , K. M. Huffenberger , C. R. Lawrence , A. E. Lange

The process of wide-field synthesis imaging is explored, with the aim of understanding the implications of variable, polarised primary beams for forthcoming Epoch of Reionisation experiments. These experiments seek to detect weak signatures…

Instrumentation and Methods for Astrophysics · Physics 2012-06-05 Daniel A. Mitchell , Randall B. Wayth , Gianni Bernardi , Lincoln J. Greenhill , Stephen M. Ord

We propose a new fast algorithm for solving one of the standard formulations of frame-based image deconvolution: an unconstrained optimization problem, involving an $\ell_2$ data-fidelity term and a non-smooth regularizer. Our approach is…

Optimization and Control · Mathematics 2016-11-17 Mario A. T. Figueiredo , Jose M. Bioucas-Dias , Manya V. Afonso

The characteristic feature of inverse problems is their instability with respect to data perturbations. In order to stabilize the inversion process, regularization methods have to be developed and applied. In this work we introduce and…

Numerical Analysis · Mathematics 2022-08-22 Andrea Ebner , Jürgen Frikel , Dirk Lorenz , Johannes Schwab , Markus Haltmeier

We introduce the first learning-based dense matching algorithm, termed Equirectangular Projection-Oriented Dense Kernelized Feature Matching (EDM), specifically designed for omnidirectional images. Equirectangular projection (ERP) images,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Dongki Jung , Jaehoon Choi , Yonghan Lee , Somi Jeong , Taejae Lee , Dinesh Manocha , Suyong Yeon

This paper characterizes the effective beams,the effective beam window functions and the associated errors for the Planck HFI detectors. The effective beam is the angular response including the effect of the optics,detectors,data processing…

Instrumentation and Methods for Astrophysics · Physics 2015-06-15 Planck Collaboration , P. A. R. Ade , N. Aghanim , C. Armitage-Caplan , M. Arnaud , M. Ashdown , F. Atrio-Barandela , J. Aumont , C. Baccigalupi , A. J. Banday , R. B. Barreiro , E. Battaner , K. Benabed , A. Benoît , A. Benoit-Lévy , J. -P. Bernard , M. Bersanelli , P. Bielewicz , J. Bobin , J. J. Bock , J. R. Bond , J. Borrill , F. R. Bouchet , J. W. Bowyer , M. Bridges , M. Bucher , C. Burigana , J. -F. Cardoso , A. Catalano , A. Challinor , A. Chamballu , R. -R. Chary , H. C. Chiang , L. -Y Chiang , P. R. Christensen , S. Church , D. L. Clements , S. Colombi , L. P. L. Colombo , F. Couchot , A. Coulais , B. P. Crill , A. Curto , F. Cuttaia , L. Danese , R. D. Davies , P. de Bernardis , A. de Rosa , G. de Zotti , J. Delabrouille , J. -M. Delouis , F. -X. Désert , J. M. Diego , H. Dole , S. Donzelli , O. Doré , M. Douspis , J. Dunkley , X. Dupac , G. Efstathiou , T. A. Enßlin , H. K. Eriksen , F. Finelli , O. Forni , M. Frailis , A. A. Fraisse , E. Franceschi , S. Galeotta , K. Ganga , M. Giard , Y. Giraud-Héraud , J. González-Nuevo , K. M. Górski , S. Gratton , A. Gregorio , A. Gruppuso , J. E. Gudmundsson , J. Haissinski , F. K. Hansen , D. Hanson , D. Harrison , S. Henrot-Versillé , C. Hernández-Monteagudo , D. Herranz , S. R. Hildebrandt , E. Hivon , M. Hobson , W. A. Holmes , A. Hornstrup , Z. Hou , W. Hovest , K. M. Huffenberger , A. H. Jaffe , T. R. Jaffe , W. C. Jones , M. Juvela , E. Keihänen , R. Keskitalo , T. S. Kisner , R. Kneissl , J. Knoche , L. Knox , M. Kunz , H. Kurki-Suonio , G. Lagache , J. -M. Lamarre , A. Lasenby , R. J. Laureijs , C. R. Lawrence , R. Leonardi , C. Leroy , J. Lesgourgues , M. Liguori , P. B. Lilje , M. Linden-Vørnle , M. López-Caniego , P. M. Lubin , J. F. Macías-Pérez , C. J. MacTavish , B. Maffei , N. Mandolesi , M. Maris , D. J. Marshall , P. G. Martin , E. Martínez-González , S. Masi , M. Massardi , S. Matarrese , T. Matsumura , F. Matthai , P. Mazzotta , P. McGehee , A. Melchiorri , L. Mendes , A. Mennella , M. Migliaccio , S. Mitra , M. -A. Miville-Deschênes , A. Moneti , L. Montier , G. Morgante , D. Mortlock , D. Munshi , J. A. Murphy , P. Naselsky , F. Nati , P. Natoli , C. B. Netterfield , H. U. Nørgaard-Nielsen , F. Noviello , D. Novikov , I. Novikov , S. Osborne , C. A. Oxborrow , F. Paci , L. Pagano , F. Pajot , D. Paoletti , F. Pasian , G. Patanchon , O. Perdereau , L. Perotto , F. Perrotta , F. Piacentini , M. Piat , E. Pierpaoli , D. Pietrobon , S. Plaszczynski , E. Pointecouteau , A. M. Polegre , G. Polenta , N. Ponthieu , L. Popa , T. Poutanen , G. W. Pratt , G. Prézeau , S. Prunet , J. -L. Puget , J. P. Rachen , M. Reinecke , M. Remazeilles , C. Renault , S. Ricciardi , T. Riller , I. Ristorcelli , G. Rocha , C. Rosset , G. Roudier , M. Rowan-Robinson , B. Rusholme , M. Sandri , D. Santos , A. Sauvé , G. Savini , D. Scott , E. P. S. Shellard , L. D. Spencer , J. -L. Starck , V. Stolyarov , R. Stompor , R. Sudiwala , F. Sureau , D. Sutton , A. -S. Suur-Uski , J. -F. Sygnet , J. A. Tauber , D. Tavagnacco , L. Terenzi , M. Tomasi , M. Tristram , M. Tucci , G. Umana , L. Valenziano , J. Valiviita , B. Van Tent , P. Vielva , F. Villa , N. Vittorio , L. A. Wade , B. D. Wandelt , D. Yvon , A. Zacchei , A. Zonca

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

An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to…

Medical Physics · Physics 2009-11-11 A Jannetta , J C Jackson , C J Kotre , I P Birch , K J Robson , R Padgett

A spatially regularized Gaussian mixture model, LapGM, is proposed for the bias field correction and magnetic resonance normalization problem. The proposed spatial regularizer gives practitioners fine-tuned control between balancing bias…

Medical Physics · Physics 2022-09-29 Luciano Vinas , Arash A. Amini , Jade Fischer , Atchar Sudhyadhom

The all-sky 408 MHz map of Haslam et al. is one the most important total-power radio surveys. It has been widely used to study diffuse synchrotron radiation from our Galaxy and as a template to remove foregrounds in cosmic microwave…

Instrumentation and Methods for Astrophysics · Physics 2015-06-11 M. Remazeilles , C. Dickinson , A. J. Banday , M. -A. Bigot-Sazy , T. Ghosh

Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution and the Bayesian posterior. Such an approximation leads to severe mode collapse and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Weimin Bai , Yuxuan Gu , Yifei Wang , Weijian Luo , He Sun

Inferring a process matrix characterizing a quantum channel from experimental measurements is a key issue of quantum information. Sometimes the noise affecting the measured counts brings to matrices very different from the expected ones and…

Quantum Physics · Physics 2024-01-31 Massimiliano Guarneri , Andrea Chiuri