4 citations · 7 across the 4 of their papers we have counts for
4 papers
AstroClearNet: Deep image prior for multi-frame astronomical image restoration
Yashil Sukurdeep, Fausto Navarro, Tamás Budavári
Recovering high-fidelity images of the night sky from blurred observations is a fundamental problem in astronomy, where traditional methods typically fall short. In ground-based as…
ImageMM: Joint multi-frame image restoration and super-resolution
Yashil Sukurdeep, Tamás Budavári, Andrew J. Connolly +1
A key processing step in ground-based astronomy involves combining multiple noisy and blurry exposures to produce an image of the night sky with an improved signal-to-noise ratio.…
A flexible Expectation-Maximization framework for fast, scalable and high-fidelity multi-frame astronomical image deconvolution
Yashil Sukurdeep, Fausto Navarro, Tamas Budavari
We present a computationally efficient expectation-maximization framework for multi-frame image deconvolution and super-resolution. Our method is well adapted for processing large…
Learning the Night Sky with Deep Generative Priors
Fausto Navarro, Daniel Hall, Tamas Budavari +1
Recovering sharper images from blurred observations, referred to as deconvolution, is an ill-posed problem where classical approaches often produce unsatisfactory results. In groun…