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Semi-discrete Optimal Transport in Patch Space for Enriching Gaussian Textures

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Book cover Geometric Science of Information (GSI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10589))

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Abstract

A bilevel texture model is proposed, based on a local transform of a Gaussian random field. The core of this method relies on the optimal transport of a continuous Gaussian distribution towards the discrete exemplar patch distribution. The synthesis then simply consists in a fast post-processing of a Gaussian texture sample, boiling down to an improved nearest-neighbor patch matching, while offering theoretical guarantees on statistical compliancy.

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Acknowledgments

This work has been partially funded by Project Texto (Projet Jeunes Chercheurs du GdR Isis).

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Authors and Affiliations

  1. Laboratoire MAP5, Université Paris Descartes and CNRS, Sorbonne Paris Cité, Paris, France

    Bruno Galerne

  2. CMLA, ENS Cachan, CNRS, Université Paris-Saclay, 94235, Cachan, France

    Arthur Leclaire

  3. Normandie Univ, ENSICAEN, CNRS, GREYC, 14000, Caen, France

    Julien Rabin

Authors
  1. Bruno Galerne
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  2. Arthur Leclaire
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  3. Julien Rabin
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Corresponding author

Correspondence to Arthur Leclaire .

Editor information

Editors and Affiliations

  1. Ecole Polytechnique, Palaiseau, France

    Frank Nielsen

  2. Thales Land and Air Systems, Limours, France

    Frédéric Barbaresco

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Galerne, B., Leclaire, A., Rabin, J. (2017). Semi-discrete Optimal Transport in Patch Space for Enriching Gaussian Textures. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2017. Lecture Notes in Computer Science(), vol 10589. Springer, Cham. https://doi.org/10.1007/978-3-319-68445-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-68445-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68444-4

  • Online ISBN: 978-3-319-68445-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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