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A huge amount of data has been acquired with the GREGOR Fabry-P\'erot Interferometer (GFPI), large-format facility cameras, and since 2016 with the High-resolution Fast Imager (HiFI). These data are processed in standardized procedures with…
We present a GPU-accelerated transient detection pipeline developed for time-domain surveys with the Dark Energy Camera (DECam). It enables real-time-capable image processing, incorporating science-driven candidate filtering to support…
In low-light conditions, a conventional camera imaging pipeline produces sub-optimal images that are usually dark and noisy due to a low photon count and low signal-to-noise ratio (SNR). We present a data-driven approach that learns the…
Rapid localisation of celestial transients like pulsars requires efficient short-timescale imaging. In radio astronomy, Fast Imaging Pipeline (FIP) addresses this need by reconstructing radio astronomical images and identifying candidates…
Graphics rendering applications increasingly leverage neural networks in tasks such as denoising, supersampling, and frame extrapolation to improve image quality while maintaining frame rates. The temporal coherence inherent in these tasks…
Transient radio sources, such as fast radio bursts, intermittent pulsars, and rotating radio transients, can offer a wealth of information regarding extreme emission physics as well as the intervening interstellar and/or intergalactic…
Optical flow provides information on relative motion that is an important component in many computer vision pipelines. Neural networks provide high accuracy optical flow, yet their complexity is often prohibitive for application at the edge…
Reconstructing dynamic, time-varying scenes with computed tomography (4D-CT) is a challenging and ill-posed problem common to industrial and medical settings. Existing 4D-CT reconstructions are designed for sparse sampling schemes that…
High-throughput imaging workflows, such as Parallel Rapid Imaging with Spectroscopic Mapping (PRISM), generate data at rates that exceed conventional real-time processing capabilities. We present a scalable FPGA-based preprocessing pipeline…
Coming high-cadence wide-field optical telescopes will image hundreds of thousands of sources per minute. Besides inspecting the near real-time data streams for transient and variability events, the accumulated data archive is a wealthy…
The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky…
In portable, three dimensional, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high quality images from a limited number of radio-frequency (RF) measurements due to receiver (Rx) or…
In recent years, consumer-level depth cameras have been adopted for various applications. However, they often produce depth maps at only a moderately high frame rate (approximately 30 frames per second), preventing them from being used for…
Software products nova.astrometry.net, SExtractor and Aladin are shown to be used for searching for transient phenomena in series of photometric images. An algorithm for taking into account atmospheric distortions introduced into images…
Strong-lensing images provide a wealth of information both about the magnified source and about the dark matter distribution in the lens. Precision analyses of these images can be used to constrain the nature of dark matter. However, this…
Radiometric infrared (IR) imaging is a valuable technique for remote-sensing applications in precision agriculture, such as irrigation monitoring, crop health assessment, and yield estimation. Low-cost uncooled non-radiometric IR cameras…
Imaging in low light is challenging due to low photon count and low SNR. Short-exposure images suffer from noise, while long exposure can induce blur and is often impractical. A variety of denoising, deblurring, and enhancement techniques…
Scientists are drawn to synchrotrons and accelerator based light sources because of their brightness, coherence and flux. The rate of improvement in brightness and detector technology has outpaced Moore's law growth seen for computers,…
Convolutional neural networks have enabled accurate image super-resolution in real-time. However, recent attempts to benefit from temporal correlations in video super-resolution have been limited to naive or inefficient architectures. In…
Most existing super-resolution methods do not perform well in real scenarios due to lack of realistic training data and information loss of the model input. To solve the first problem, we propose a new pipeline to generate realistic…