Real-Time Analysis of Large Astronomical Images
K. Kuehn, R. Hupe

TL;DR
This paper introduces ImageHealth, a fast, accurate, instrument-independent software tool for real-time analysis of large astronomical images, supporting high-cadence surveys like the Dark Energy Survey.
Contribution
The paper presents ImageHealth, a new real-time image processing tool that is faster than standard methods while maintaining accuracy, suitable for large-scale astronomical surveys.
Findings
ImageHealth achieves comparable accuracy to SourceExtractor.
ImageHealth runs significantly faster than SourceExtractor.
The software is instrument-independent and freely available.
Abstract
Forthcoming instruments designed for high-cadence large-area surveys, such as the Dark Energy Survey and Large Synoptic Survey Telescope, will generate several GB of data products every few minutes during survey operations. Since such surveys are designed to operate with minimal observer interaction, automated real-time analysis of these large images is necessary to ensure uninterrupted production of science-quality data. We describe a software infrastructure suite designed to support such surveys, focusing particularly on ImageHealth, a tool for near-real-time processing of large images. These image manipulation and analysis algorithms were applied to simulated data from the Dark Energy Survey, as well as observed data collected by the Y4KCam on the CTIO 1m telescope and the Mosaic camera on the Blanco telescope. The accuracy and speed of the ImageHealth code in particular were…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Adaptive optics and wavefront sensing · CCD and CMOS Imaging Sensors
