5 papers
Variational Deep Unfolding with Mamba-Based Nonlocal Modeling for Underwater Image Enhancement
Daniel Torres, Julia Navarro, Catalina Sbert +1
Underwater imaging plays a crucial role in ocean engineering, although captured data often suffer from poor visibility and color distortion. To address these challenges, we propose…
On the Equivariant Learning of the -tensor Order Parameter
Julia Navarro, Mark Wilkinson
We construct and evaluate group-equivariant neural networks for the prediction of the two-dimensional -tensor order parameter of nematic liquid crystals from synthetically gener…
Nonlocal Retinex-Based Variational Model and its Deep Unfolding Twin for Low-Light Image Enhancement
Daniel Torres, Joan Duran, Julia Navarro +1
Images captured under low-light conditions present significant limitations in many applications, as poor lighting can obscure details, reduce contrast, and hide noise. Removing the…
Super-Resolution of Sentinel-2 Images Using a Geometry-Guided Back-Projection Network with Self-Attention
Ivan Pereira-Sánchez, Daniel Torres, Francesc Alcover +4
The Sentinel-2 mission provides multispectral imagery with 13 bands at resolutions of 10m, 20m, and 60m. In particular, the 10m bands offer fine structural detail, while the 20m ba…
Model-Guided Network with Cluster-Based Operators for Spatio-Spectral Super-Resolution
Ivan Pereira-Sánchez, Julia Navarro, Ana Belén Petro +1
This paper addresses the problem of reconstructing a high-resolution hyperspectral image from a low-resolution multispectral observation. While spatial super-resolution and spectra…