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Compressed sensing is an image reconstruction technique to achieve high-quality results from limited amount of data. In order to achieve this, it utilizes prior knowledge about the samples that shall be reconstructed. Focusing on image…

It is shown how to apply the Maximum Entropy Method (MEM) to numerical Dyson-Schwinger studies for the extraction of spectral functions of correlators from their corresponding Euclidean propagators. Differences to the application in lattice…

High Energy Physics - Phenomenology · Physics 2008-11-26 Dominik Nickel

We present a combined maximum-entropy method (MEM) and Mexican Hat wavelet (MHW) analysis in order to recover the different components of the microwave sky. We apply this technique to simulated observations by the ESA Planck satellite in…

Reconstructing 4D or 6D phase space distributions from 1D or 2D measurements is a challenging inverse problem encountered in particle accelerators. Entropy maximization is an established method to incorporate prior information in the…

Accelerator Physics · Physics 2025-08-18 Austin Hoover

Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal…

Scanning Electron Microscopy (SEM) is pivotal in revealing intricate micro- and nanoscale features across various research fields. However, obtaining high-resolution SEM images presents challenges, including prolonged scanning durations and…

Image and Video Processing · Electrical Eng. & Systems 2024-10-08 Tom Reclik , Setareh Medghalchi , Philipp Schumacher , Maximilian Wollenweber , Talal Al-Samman , Sandra Korte-Kerzel , Ulrich Kerzel

A flexible maximum-entropy component separation algorithm is presented that accommodates anisotropic noise, incomplete sky-coverage and uncertainties in the spectral parameters of foregrounds. The capabilities of the method are determined…

Scanning Transmission Electron Microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In…

Instrumentation and Detectors · Physics 2019-01-15 Xin Li , Ondrej Dyck , Sergei V. Kalinin , Stephen Jesse

An iterative method is derived for image reconstruction. Among other attributes, this method allows constraints unrelated to the radiation measurements to be incorporated into the reconstructed image. A comparison is made with the widely…

Computational Physics · Physics 2011-01-06 Clinton DeW. Van Siclen

Sampling from constrained distributions has a wide range of applications, including in Bayesian optimization and robotics. Prior work establishes convergence and feasibility guarantees for constrained sampling, but assumes that the feasible…

Machine Learning · Computer Science 2026-05-13 Cornelius V. Braun , Tilman Burghoff , Marc Toussaint

Maximum-likelihood methods are applied to the problem of absorption tomography. The reconstruction is done with the help of an iterative algorithm. We show how the statistics of the illuminating beam can be incorporated into the…

Data Analysis, Statistics and Probability · Physics 2009-11-07 J. Rehacek , Z. Hradil , M. Zawisky , W. Treimer , M. Strobl

Objective:Optoacoustic (photoacoustic) tomography is aimed at reconstructing maps of the initial pressure rise induced by the absorption of light pulses in tissue. In practice, due to inaccurate assumptions in the forward model, noise and…

Medical Physics · Physics 2019-01-21 Jaya Prakash , Subhamoy Mandal , Daniel Razansky , Vasilis Ntziachristos

An alternative approach to the image simulation in high resolution transmission electron microscopy (HRTEM) is introduced after comparative analysis of the existing image simulation methods. The alternative method is based on considering…

Materials Science · Physics 2021-03-30 Usha Bhat , Ranjan Datta

Purpose: Although recent deep energy-based generative models (EBMs) have shown encouraging results in many image generation tasks, how to take advantage of the self-adversarial cogitation in deep EBMs to boost the performance of Magnetic…

Image and Video Processing · Electrical Eng. & Systems 2021-09-10 Yu Guan , Zongjiang Tu , Shanshan Wang , Qiegen Liu , Yuhao Wang , Dong Liang

The CLEAN deconvolution algorithm has well-known limitations due to the restriction of locating point source model components on a discretized grid. In this letter we demonstrate that these limitations are even more pronounced when applying…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 M. R. Bell , N. Oppermann , A. Crai , T. A. Enßlin

Compressive sampling is a new paradigm for sampling, based on sparseness of signals or signal representations. It is much less restrictive than Nyquist-Shannon sampling theory and thus explains and systematises the widespread experience…

Instrumentation and Methods for Astrophysics · Physics 2015-05-28 Feng Li , Tim J. Cornwell , Frank de Hoog

Single-particle electron cryomicroscopy is an essential tool for high-resolution 3D reconstruction of proteins and other biological macromolecules. An important challenge in cryo-EM is the reconstruction of non-rigid molecules with parts…

Image and Video Processing · Electrical Eng. & Systems 2021-05-31 Amit Moscovich , Amit Halevi , Joakim Andén , Amit Singer

Extracting reference spectra, or endmembers (EMs) from a given multi- or hyperspectral image, as well as estimating the size of the EM set, plays an important role in multispectral image processing. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2018-09-27 Christoph Schikora , Markus Plack , Andreas Kolb

This paper discusses the reconstruction of partially sampled spectrum-images to accelerate the acquisition in scanning transmission electron microscopy (STEM). The problem of image reconstruction has been widely considered in the literature…

Image and Video Processing · Electrical Eng. & Systems 2020-02-05 Etienne Monier , Thomas Oberlin , Nathalie Brun , Xiaoyan Li , Marcel Tencé , Nicolas Dobigeon