Volume 64, 2018SMAI 2017 - 8e Biennale Française des Mathématiques Appliquées et Industrielles
|Page(s)||37 - 53|
|Published online||20 November 2018|
Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion
CNRS, LJLL, Université Pierre et Marie Curie, Paris, France
2 Équipe INRIA Paris CAGE
3 SYSTEC, FEUP, University of Porto, Portugal
4 Samara University, Russia
5 LSIS, Université de Toulon, France
6 CRNS, L2S, CentraleSupélec, Gif-sur-Yvette, France
7 CMAP, École Polytechnique, Palaiseau, France
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.
© EDP Sciences, SMAI 2018
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