PIERRE, Fabien; AUJOL, Jean-François

doi:10.1007/978-3-030-03009-4_55-1

Métadonnées

Licence d’utilisation du document

PIERRE, Fabien
Augmentation visuelle d'environnements complexes [MAGRIT-POST]
Visual Augmentation of Complex Environments [MAGRIT]

AUJOL, Jean-François
Institut de Mathématiques de Bordeaux [IMB]

Langue

Chapitre d'ouvrage

Ce document a été publié dans

Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. 2020

Date de soutenance

2020

Résumé en anglais

In the last years, image and video colorization has been considered from many points of view. The technique consists in the addition of a color component to a gray-scale image. This operation needs additional priors which can be given by manual intervention of the user from an example image or be extracted from a large dataset of color images. A very large variety of approaches has been used to solve this problem, like PDE models, non-local methods, variational frameworks, learning approaches, etc. In this chapter, we aim at providing a general overview of state-of-the-art approaches with a focus on few representative methods. Moreover, some recent techniques from the different types of priors (manual, exemplar-based, dataset-based) are explained and compared. The organization of the chapter aims at describing the evolution of the techniques in relation to each other. A focus on some efficient strategies is proposed for each kind of methodology.< Réduire

URI

https://oskar-bordeaux.fr/handle/20.500.12278/191807

DOI

http://dx.doi.org/10.1007/978-3-030-03009-4_55-1

Project ANR

Repenser la post-production d'archives avec des méthodes à patch, variationnelles et par apprentissage - ANR-19-CE23-0027

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251