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Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae. Analysing and processing these images can reveal intricate internal structures of these objects, allowing researchers to…
In this paper, we present a novel approach to the estimation of strongly varying backgrounds in astronomical images by means of small objects removal and subsequent missing pixels interpolation. The method is based on the analysis of a…
We present a new methodology for the estimation of stellar atmospheric parameters from narrow- and intermediate-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS), and propose a method for target pre-selection of…
Image datasets serve as the foundation for machine learning models in computer vision, significantly influencing model capabilities, performance, and biases alongside architectural considerations. Therefore, understanding the composition…
Polarization information of the light can provide rich cues for computer vision and scene understanding tasks, such as the type of material, pose, and shape of the objects. With the advent of new and cheap polarimetric sensors, this imaging…
Hyperspectral cameras provide numerous advantages in terms of the utility of the data captured. They capture hundreds of data points per sample (pixel) instead of only the few of RGB or multispectral camera systems. Aerial systems sense…
Astrophotonics lies at the interface of astronomy and photonics. This burgeoning field -- now formally recognized by the optics community -- has emerged over the past decade in response to the increasing demands of astronomical…
We have created a new image analysis pipeline to reprocess images taken by the Near Earth Asteroid Tracking survey and have applied it to ten nights of observations. This work is the first large-scale reprocessing of images from an asteroid…
Astrometric jitter noise arises when starspots on a rotating stellar surface move in and out of view, shifting the photocenter. This noise may limit our ability to detect and weigh small, sub-Neptune-sized planets around active stars. By…
Astrophotonics is the application of versatile photonic technologies to channel, manipulate, and disperse guided light from one or more telescopes to achieve scientific objectives in astronomy in an efficient and cost-effective way. The…
orbitize! is an open-source, object-oriented software package for fitting the orbits of directly-imaged objects. It packages the Orbits for the Impatient (OFTI) algorithm and a parallel-tempered Markov Chain Monte Carlo (MCMC) algorithm…
The Cosmic Infrared Background ExpeRiment (CIBER) is a rocket-borne absolute photometry imaging and spectroscopy experiment optimized to detect signatures of first-light galaxies present during reionization in the unresolved IR background.…
In this paper we deal with the problem of chromaticity, i.e. apparent position variation of stellar images with their spectral distribution, using neural networks to analyse and process astronomical images. The goal is to remove this…
We present an open-source Julia-based software toolkit for solving the phase problem using dual-space iterative algorithms. The toolkit is specifically designed for aperiodic crystals and quasicrystals, supporting general space group…
We present infrared photometry of all 36 potential JWST calibrators for which there is archival Spitzer IRAC data. This photometry can then be used to inform stellar models necessary to provide absolute calibration for all JWST instruments.…
The science investigation teams (SITs) for the WFIRST coronagraphic instrument have begun studying the capabilities of the instrument to directly image reflected light off from exoplanets at contrasts down to contrasts of ~10^-9 with…
Astronomical telescopes suffer from a tradeoff between field of view (FoV) and image resolution: increasing the FoV leads to an optical field that is under-sampled by the science camera. This work presents a novel computational imaging…
We address the problem of discretizing continuous cosmological signals such as a galaxy distribution for further processing with Fast Fourier techniques. Discretizing, in particular representing continuous signals by discrete sets of sample…
Modern computer systems typically conbine multicore CPUs with accelerators like GPUs for inproved performance and energy efficiency. However, these sys- tems suffer from poor performance portability, code tuned for one device must be…
AOtools is a Python package which is open-source and aimed at providing tools for adaptive optics users and researchers. We present version 1.0 which contains tools for adaptive optics processing, including analysing data in the pupil…