metadata
license: mit
Description
This repository contains a series of weights for adapting the DRUNet denoiser in order to be able to work with hyperspectral images.
These weights are meant to be used with the hypnp library:
http://github.com/Danaroth83/hypnp
In particular the weights contained in this folder are associated to the following adapting architecture:
20251025_174116_606035-projection_encoder: An encoding/decoder network.20251029_110345_695678-projection_qr: A QR decomposition encoder and deep decoder network.20251026_035736_830488-grouper_arranger: A band selection module.20251026_044313_346452-grouper_arranger_skip: A band selection module with skip attention network.20251026_141518_492696-film_middle: A FiLM that hooks middle layers of the DRUNet. Baseline result.20251026_063231_578169-film_middle_qr: FiLM network with QR projection of the input.20251027_091506_635645-film_middle_qr_groups_10: FiLM network with QR projection, with inputs passed sequentially in groups of 10.20251029_093111_154168-film_no_head: FiLM network without trained head in DRUNet.
Credits
These weights were produced by:
Daniele Picone
Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble, France
Mail: daniele.picone@grenoble-inp.fr
Mohamad Jouni
Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble, France
Mail: mohamad.jouni@grenoble-inp.fr