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Learning to Denoise Astronomical Images with U-nets
[article]
2020
arXiv
pre-print
Astronomical images are essential for exploring and understanding the universe. Optical telescopes capable of deep observations, such as the Hubble Space Telescope, are heavily oversubscribed in the Astronomical Community. Images also often contain additive noise, which makes de-noising a mandatory step in post-processing the data before further data analysis. In order to maximise the efficiency and information gain in the post-processing of astronomical imaging, we turn to machine learning. We
arXiv:2011.07002v1
fatcat:d4yv7xt2xzaoxdhi7qoouk5f7q