no code implementations • 2 Nov 2023 • Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez, Reuben A. Farrugia
In this work we test the ability of deep learning methods to provide an end-to-end mapping between low and high resolution images applying it to the iris recognition problem.
1 code implementation • 26 Jan 2023 • Tomasz Tarasiewicz, Jakub Nalepa, Reuben A. Farrugia, Gianluca Valentino, Mang Chen, Johann A. Briffa, Michal Kawulok
For Sentinel-2, spectral information fusion allows for enhancing the 20 m and 60 m bands to the 10 m resolution.
1 code implementation • Sensors 2023 • Matthew Aquilina, Keith George Ciantar, Christian Galea, Kenneth P. Camilleri, Reuben A. Farrugia, John Abela
To date, the best-performing blind super-resolution (SR) techniques follow one of two paradigms: A) generate and train a standard SR network on synthetic low-resolution - high-resolution (LR - HR) pairs or B) attempt to predict the degradations an LR image has suffered and use these to inform a customised SR network.
no code implementations • 18 Oct 2022 • Fernando Alonso-Fernandez, Reuben A. Farrugia, Josef Bigun
Current research in iris recognition is moving towards enabling more relaxed acquisition conditions.
no code implementations • PVLAM (LREC) 2022 • Marc Tanti, Shaun Abdilla, Adrian Muscat, Claudia Borg, Reuben A. Farrugia, Albert Gatt
To encourage the development of more human-focused descriptions, we developed a new data set of facial descriptions based on the CelebA image data set.
no code implementations • 12 Apr 2022 • Fernando Alonso-Fernandez, Reuben A. Farrugia, Julian Fierrez, Josef Bigun
Such techniques are designed to restore generic images and therefore do not exploit the specific structure found in biometric images (e. g. iris or faces), which causes the solution to be sub-optimal.
1 code implementation • IEEE Signal Processing Letters 2021 • Matthew Aquilina, Christian Galea, John Abela, Kenneth P. Camilleri, Reuben A. Farrugia
While many such networks can upscale low-resolution (LR) images using just the raw pixel-level information, the ill-posed nature of SR can make it difficult to accurately super-resolve an image which has undergone multiple different degradations.
no code implementations • 27 Sep 2018 • Reuben A. Farrugia, C. Guillemot
Super-resolving this principal basis using an SISR method allows us to super-resolve all the information that is coherent across the entire light field.
1 code implementation • LREC 2018 • Albert Gatt, Marc Tanti, Adrian Muscat, Patrizia Paggio, Reuben A. Farrugia, Claudia Borg, Kenneth P. Camilleri, Mike Rosner, Lonneke van der Plas
To gain a better understanding of the variation we find in face description and the possible issues that this may raise, we also conducted an annotation study on a subset of the corpus.
no code implementations • 12 Jan 2018 • Reuben A. Farrugia, Christine Guillemot
Light field imaging has recently known a regain of interest due to the availability of practical light field capturing systems that offer a wide range of applications in the field of computer vision.