An Interpolating Distance Between Optimal Transport and Fisher–Rao Metrics

  • Lénaïc Chizat
  • Gabriel Peyré
  • Bernhard Schmitzer
  • François-Xavier Vialard
Article

Abstract

This paper defines a new transport metric over the space of nonnegative measures. This metric interpolates between the quadratic Wasserstein and the Fisher–Rao metrics and generalizes optimal transport to measures with different masses. It is defined as a generalization of the dynamical formulation of optimal transport of Benamou and Brenier, by introducing a source term in the continuity equation. The influence of this source term is measured using the Fisher–Rao metric and is averaged with the transportation term. This gives rise to a convex variational problem defining the new metric. Our first contribution is a proof of the existence of geodesics (i.e., solutions to this variational problem). We then show that (generalized) optimal transport and Hellinger metrics are obtained as limiting cases of our metric. Our last theoretical contribution is a proof that geodesics between mixtures of sufficiently close Dirac measures are made of translating mixtures of Dirac masses. Lastly, we propose a numerical scheme making use of first-order proximal splitting methods and we show an application of this new distance to image interpolation.

Keywords

Unbalanced optimal transport Wasserstein \(L^2\) metric Fisher–Rao metric Positive Radon measures 

Mathematics Subject Classification

49-XX 

Notes

Acknowledgments

The work of Bernhard Schmitzer has been supported by the Fondation Sciences Mathématiques de Paris. The work of Gabriel Peyré has been supported by the European Research Council (ERC project SIGMA-Vision). We would like to thank Yann Brenier and Jean-David Benamou for stimulating discussions.

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Copyright information

© SFoCM 2016

Authors and Affiliations

  • Lénaïc Chizat
    • 1
  • Gabriel Peyré
    • 1
  • Bernhard Schmitzer
    • 1
  • François-Xavier Vialard
    • 1
  1. 1.Project team Mokaplan, CEREMADE, CNRS, INRIAUniversité Paris-DauphineParisFrance

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