4 papers
Deep priors for satellite image restoration with accurate uncertainties
Biquard Maud, Marie Chabert, Florence Genin +2
Satellite optical images, upon their on-ground receipt, offer a distorted view of the observed scene. Their restoration, including denoising, deblurring, and sometimes super-resolu…
Variational Bayes image restoration with compressive autoencoders
Maud Biquard, Marie Chabert, Florence Genin +2
Regularization of inverse problems is of paramount importance in computational imaging. The ability of neural networks to learn efficient image representations has been recently ex…
Joint attitude estimation and 3D neural reconstruction of non-cooperative space objects
Clément Forray, Pauline Delporte, Nicolas Delaygue +2
Obtaining a better knowledge of the current state and behavior of objects orbiting Earth has proven to be essential for a range of applications such as active debris removal, in-or…
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems
Maud Biquard, Marie Chabert, Florence Genin +2
Poisson-Gaussian noise describes the noise of various imaging systems thus the need of efficient algorithms for Poisson-Gaussian image restoration. Deep learning methods offer stat…