Related papers: Experience of high resolution VLBI imaging using g…
Deep learning-based methods have shown remarkable success for various image restoration tasks such as denoising and deblurring. The current state-of-the-art networks are relatively deep and utilize (variants of) self attention mechanisms.…
This work presents an abstract framework for the design, implementation, and analysis of the multiscale spectral generalized finite element method (MS-GFEM), a particular numerical multiscale method originally proposed in [I. Babuska and R.…
Radio Environment Maps (REMs) have the potential to serve as an important enabler for intelligent modeling and control in emerging AI-native 6G networks. Despite significant progress, most REM construction methods remain passive, relying on…
The Extreme Deconvolution method fits a probability density to a dataset where each observation has Gaussian noise added with a known sample-specific covariance, originally intended for use with astronomical datasets. The existing fitting…
The Disp method is an algorithm that is used for reconstruction of primary gamma ray direction in ground- based atmospheric Cherenkov telescope experiments -measuring very-high-energy (VHE) gamma rays in the energy range between 100GeV and…
A key processing step in ground-based astronomy involves combining multiple noisy and blurry exposures to produce an image of the night sky with an improved signal-to-noise ratio. Typically, this is achieved via image coaddition, and can be…
The generalized linear system (GLS) has been widely used in wireless communications to evaluate the effect of nonlinear preprocessing on receiver performance. Generalized approximation message passing (AMP) is a state-of-the-art algorithm…
A simple X-ray imaging system using off-the-shelf electronics and simple reconstruction algorithms aiming a spatial resolution of 1.7 mm ($\sim 3\,\%$ of the detector length) is described in this work. For this, two 100 cm$^2$ Gas Electron…
Astrophysical sources such as radio halos and relics in galaxy clusters, supernova remnants and radio galaxies have angular sizes from a few to several $10$s of arcminutes. In radio interferometric imaging of such sources, the largest…
The Earth Occultation Technique (EOT) has been applied to Fermi's Gamma-ray Burst Monitor (GBM) to perform all-sky monitoring for a predetermined catalog of hard X-ray/soft gamma-ray sources. In order to search for sources not in the…
Popularized by their strong image generation performance, diffusion and related methods for generative modeling have found widespread success in visual media applications. In particular, diffusion methods have enabled new approaches to data…
Deep space navigation presents significant challenges due to the unavailability of Global Navigation Satellite System (GNSS) signals and severe signal attenuation over interplanetary distances. Traditional terrestrial systems, such as NASA…
Scanning Electron Microscopy (SEM) images often suffer from noise contamination, which degrades image quality and affects further analysis. This research presents a complete approach to estimate their Signal-to-Noise Ratio (SNR) and noise…
Purpose: Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization…
We propose the multi-frequency synthesis (MFS) algorithm with spectral correction of frequency-dependent source brightness distribution based on maximum entropy method. In order to take into account the spectral terms of n-th order in the…
In this work, we propose a generalized multiscale inversion algorithm for heterogeneous problems that aims at solving an inverse problem on a computational coarse grid. Previous inversion techniques for multiscale problems seek a…
Super-resolution without explicit sub-pixel motion estimation is a very active subject of image reconstruction containing general motion. The Non-Local Means (NLM) method is a simple image reconstruction method without explicit motion…
In recent deep image compression neural networks, the entropy model plays a critical role in estimating the prior distribution of deep image encodings. Existing methods combine hyperprior with local context in the entropy estimation…
We present preliminary results from the deepest VLBI observations yet conducted. VLBA+GBT 1.4 GHz observations of a region within NOAO-N, reach an r.m.s. noise level of 9 microJy per beam. Three sources are clearly detected (> 7 sigma)…
The Gaussian Process Latent Variable Model (GP-LVM) is a non-linear probabilistic method of embedding a high dimensional dataset in terms low dimensional `latent' variables. In this paper we illustrate that maximum a posteriori (MAP)…