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

Abstract : 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.
Type de document :
Pré-publication, Document de travail
2018
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https://hal.archives-ouvertes.fr/hal-01721718
Contributeur : Dario Prandi <>
Soumis le : vendredi 2 mars 2018 - 14:26:05
Dernière modification le : vendredi 16 novembre 2018 - 01:51:46

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  • HAL Id : hal-01721718, version 1
  • ARXIV : 1801.03800

Citation

Ugo Boscain, Roman Chertovskih, Jean-Paul Gauthier, Dario Prandi, Alexey Remizov. Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion. 2018. 〈hal-01721718〉

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