Related papers: AstroImageJ: Image Processing and Photometric Extr…
Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. The new panchromatic, synoptic sky surveys require advanced tools for discovering patterns and trends hidden…
We developed a Python based framework for astronomical image processing and analysis. Astronomical image loading, normalizing, stacking, and filtering processes represent visible range images from grayscale. Besides, the blending process…
Advancements in technology and reduction in it's cost have led to a substantial growth in the quality & quantity of imagery captured by Earth Observation (EO) satellites. This has presented a challenge to the efficacy of the traditional…
Gaia is a revolutionary space mission developed by ESA and is delivering 5 parameter astrometry, photometry and radial velocities over the whole sky with astrometric accuracies down to a few tens of micro-arcseconds. A weakness of Gaia is…
The Gemini Planet Imager (GPI) has as its science instrument an infrared integral field spectrograph/polarimeter (IFS). Integral field spectrographs are scientificially powerful but require sophisticated data reduction systems. For GPI to…
J-PLUS is an ongoing 12-band photometric optical survey, observing thousands of square degrees of the Northern hemisphere from the dedicated JAST/T80 telescope at the Observatorio Astrof\'isico de Javalambre. T80Cam is a 2 sq.deg…
To reduce and analyze astronomical images, astronomers can rely on a wide range of libraries providing low-level implementations of legacy algorithms. However, combining these routines into robust and functional pipelines requires a major…
We have designed and implemented a novel way to process wide-field astronomical data within a distributed environment of hardware resources and humanpower. The system is characterized by integration of archiving, calibration, and…
Super-resolution imaging has revolutionized the study of systems ranging from molecular structures to distant galaxies. However, existing super-resolution methods require extensive calibration and retraining for each imaging setup, limiting…
Astronomy depends on ever increasing computing power. Processor clock-rates have plateaued, and increased performance is now appearing in the form of additional processor cores on a single chip. This poses significant challenges to the…
We introduce and publicly release a new code, ADAPTSMOOTH, which serves to smooth astronomical images in an adaptive fashion, in order to enhance the signal-to-noise ratio (S/N). The adaptive smoothing scheme allows to take full advantage…
Gaia is ESA's ambitious space astrometry mission the main objective of which is to astrometrically and spectro-photometrically map 1000 Million celestial objects (mostly in our galaxy) with unprecedented accuracy. The announcement of…
We present A-PHOT, a new publicly available code for performing aperture photometry on astronomical images, that is particularly well suited for multi-band extragalactic surveys. A-PHOT estimates the fluxes emitted by astronomical objects…
JASMINE is a Japanese planned space mission that aims to reveal the formation history of our Galaxy and discover habitable exoEarths. For these objectives, the JASMINE satellite performs high-precision astrometric observations of the…
Images from adaptive optics systems are generally affected by significant distortions of the point spread function (PSF) across the field of view, depending on the position of natural and artificial guide stars. Image reduction techniques…
We present T-PHOT, a publicly available software aimed at extracting accurate photometry from low-resolution images of deep extragalactic fields, where the blending of sources can be a serious problem for the accurate and unbiased…
As Earth science enters the era of big data, artificial intelligence (AI) not only offers great potential for solving geoscience problems, but also plays a critical role in accelerating the understanding of the complex, interactive, and…
Aerial scene classification, which aims to automatically label an aerial image with a specific semantic category, is a fundamental problem for understanding high-resolution remote sensing imagery. In recent years, it has become an active…
Here we report on a set of programs developed at the ZMBH Bio-Imaging Facility for tracking real-life images of cellular processes. These programs perform 1) automated tracking; 2) quantitative and comparative track analyses of different…
Across all disciplines that work with image data - from astrophysics to medical research and historic preservation - there is a growing need for efficient ways to browse and inspect large sets of high-resolution images. We present the…