Optimal transport between GMM for multiscale texture synthesis - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Optimal transport between GMM for multiscale texture synthesis

Julie Delon
Agnès Desolneux
Laurent Facq
Arthur Leclaire

Résumé

Using optimal transport in image processing tasks has become very popular. However, it still faces difficult computational issues when dealing with high-dimensional distributions. We propose here to use the recently introduced GMM-OT formulation, which consists in restricting the optimal transport problem to the set of Gaussian mixture models. As a proof of concept, we use it to improve the texture model Texto based on optimal transport between distributions of image patches. Using GMM-OT in this texture model allows to deal with larger patches, hence providing results with better geometric details. This new model allows for synthesis, mixing, and style transfer.
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Dates et versions

hal-03613622 , version 1 (18-03-2022)
hal-03613622 , version 2 (01-06-2023)

Identifiants

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Julie Delon, Agnès Desolneux, Laurent Facq, Arthur Leclaire. Optimal transport between GMM for multiscale texture synthesis. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), Luca Calatroni; Marco Donatelli; Serena Morigi; Marco Prato; Giuseppe Rodriguez; Matteo Santacesaria, May 2023, Cagliari, Italy. ⟨10.1007/978-3-031-31975-4_48⟩. ⟨hal-03613622v2⟩
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