A Wasserstein-type distance in the space of Gaussian Mixture Models - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue SIAM Journal on Imaging Sciences Année : 2020

A Wasserstein-type distance in the space of Gaussian Mixture Models

Julie Delon
Agnès Desolneux
  • Fonction : Auteur
  • PersonId : 927839

Résumé

In this paper we introduce a Wasserstein-type distance on the set of Gaussian mixture models. This distance is defined by restricting the set of possible coupling measures in the optimal transport problem to Gaussian mixture models. We derive a very simple discrete formulation for this distance, which makes it suitable for high dimensional problems. We also study the corresponding multi-marginal and barycenter formulations. We show some properties of this Wasserstein-type distance, and we illustrate its practical use with some examples in image processing.
Fichier principal
Vignette du fichier
WassersteinGMM-arxiv-final2.pdf (8.11 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02178204 , version 1 (09-07-2019)
hal-02178204 , version 2 (27-10-2019)
hal-02178204 , version 3 (09-05-2020)
hal-02178204 , version 4 (09-06-2020)

Identifiants

Citer

Julie Delon, Agnès Desolneux. A Wasserstein-type distance in the space of Gaussian Mixture Models. SIAM Journal on Imaging Sciences, 2020, 13 (2), pp.936-970. ⟨10.1137/19M1301047⟩. ⟨hal-02178204v4⟩
1305 Consultations
949 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More