BERTIN , Emmanuel

Observatories and satellites around the globe produce tremendous amounts of imaging data to study many different astrophysical phenomena. The serendipitous observations of Solar System objects are a fortunate by-product which have often been neglected due to the lack of a simple yet efficient identification algorithm. Meanwhile, the...

ABSTRACT We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated data, our method processes a sliding sequence of short-exposure (∼0.2 s) stellar field images to reconstruct an image devoid of both turbulence and noise. We...

Now that large databases of resolved galaxy images are provided by modern imaging surveys, advanced morphological studies can be envisioned, urging for well defined calibration samples. We present the EFIGI catalogue, a multiwavelength database specifically designed for a dense sampling of all Hubble types. The catalogue merges data from...