Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion - Archive ouverte HAL
Communication Dans Un Congrès Année : 2018

Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion

Résumé

In this paper we review several algorithms for image inpainting based on the hypoelliptic diffusion naturally associated with a mathematical model of the primary visual cortex. In particular, we present one algorithm that does not exploit the information of where the image is corrupted, and others that do it. While the first algorithm is able to reconstruct only images that our visual system is still capable of recognize, we show that those of the second type completely transcend such limitation providing reconstructions at the state-of-the-art in image inpainting. This can be interpreted as a validation of the fact that our visual cortex actually encodes the first type of algorithm.
Fichier principal
Vignette du fichier
prandi_smai2017.pdf (3.9 Mo) Télécharger le fichier
Origine Accord explicite pour ce dépôt
Loading...

Dates et versions

hal-01721718 , version 1 (23-05-2020)

Identifiants

Citer

Ugo Boscain, Roman Chertovskih, Jean-Paul Gauthier, Dario Prandi, Alexey Remizov. Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion. SMAI 2017 - 8e Biennale Française des Mathématiques Appliquées et Industrielles, Jun 2017, La Tremblade, France. pp.37 - 53, ⟨10.1051/proc/201864037⟩. ⟨hal-01721718⟩
456 Consultations
65 Téléchargements

Altmetric

Partager

More