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Pré-Publication, Document De Travail Année : 2022

Optimal Transport Between GMM for Texture Synthesis

Julie Delon
Agnès Desolneux
  • Fonction : Auteur

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 revisit 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

  • HAL Id : hal-03613622 , version 1

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Arthur Leclaire, Julie Delon, Agnès Desolneux. Optimal Transport Between GMM for Texture Synthesis. 2022. ⟨hal-03613622v1⟩
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