Scale Space and Variational Methods in Computer Vision

5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings

  • Jean-François Aujol
  • Mila Nikolova
  • Nicolas Papadakis
Conference proceedings SSVM 2015

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9087)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 9087)

Table of contents

  1. Front Matter
    Pages I-XV
    PDF

  2. Scale Space and Partial Differential Equations Methods

    1. Front Matter
      Pages 1-1
      PDF
    2. Scale-Space Theory for Auditory Signals
      Tony Lindeberg, Anders Friberg
      Pages 3-15
    3. Spectral Representations of One-Homogeneous Functionals
      Martin Burger, Lina Eckardt, Guy Gilboa, Michael Moeller
      Pages 16-27
    4. The Morphological Equivalents of Relativistic and Alpha-Scale-Spaces
      Martin Schmidt, Joachim Weickert
      Pages 28-39
    5. New Approximation of a Scale Space Kernel on SE(3) and Applications in Neuroimaging
      Jorg Portegies, Gonzalo Sanguinetti, Stephan Meesters, Remco Duits
      Pages 40-52
    6. Partial Differential Equations of Bivariate Median Filters
      Martin Welk
      Pages 53-65
    7. Fundamentals of Non-Local Total Variation Spectral Theory
      Jean-François Aujol, Guy Gilboa, Nicolas Papadakis
      Pages 66-77
    8. Morphological Scale-Space Operators for Images Supported on Point Clouds
      Jesús Angulo
      Pages 78-89
    9. Separable Time-Causal and Time-Recursive Spatio-Temporal Receptive Fields
      Tony Lindeberg
      Pages 90-102
    10. A Linear Scale-Space Theory for Continuous Nonlocal Evolutions
      Giovanno Marcelo Cárdenas, Joachim Weickert, Sarah Schäffer
      Pages 103-114

  3. Denoising, Restoration and Reconstruction

    1. Front Matter
      Pages 115-115
      PDF
    2. Bilevel Image Denoising Using Gaussianity Tests
      Jérôme Fehrenbach, Mila Nikolova, Gabriele Steidl, Pierre Weiss
      Pages 117-128
    3. On Debiasing Restoration Algorithms: Applications to Total-Variation and Nonlocal-Means
      Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon
      Pages 129-141
    4. Cartoon-Texture-Noise Decomposition with Transport Norms
      Christoph Brauer, Dirk Lorenz
      Pages 142-153
    5. Compressing Images with Diffusion- and Exemplar-Based Inpainting
      Pascal Peter, Joachim Weickert
      Pages 154-165
    6. Some Nonlocal Filters Formulation Using Functional Rearrangements
      Gonzalo Galiano, Julián Velasco
      Pages 166-177
    7. Total Variation Restoration of Images Corrupted by Poisson Noise with Iterated Conditional Expectations
      Rémy Abergel, Cécile Louchet, Lionel Moisan, Tieyong Zeng
      Pages 178-190
    8. Regularization with Sparse Vector Fields: From Image Compression to TV-type Reconstruction
      Eva-Maria Brinkmann, Martin Burger, Joana Grah
      Pages 191-202
    9. Solution-Driven Adaptive Total Variation Regularization
      Frank Lenzen, Johannes Berger
      Pages 203-215

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 5th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2015, held in Lège-Cap Ferret, France, in May 2015. The 56 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in the following topical sections: scale space and partial differential equation methods; denoising, restoration and reconstruction, segmentation and partitioning; flow, motion and registration; photography, texture and color processing; shape, surface and 3D problems; and optimization theory and methods in imaging.

Keywords

Computer graphics Computer vision Computer vision problems Contextual enhancement Feature selection Image processing Image segmentation Lie groups Mathematical optimization Minimal surface problem MPEG decompression Nonlinear eigenfunctions Partial differential equations Registration Semantic scene understanding Shape modeling Spectral total variation Surface approximation Texture synthesis Variational methods

Editors and affiliations

  • Jean-François Aujol
    • 1
  • Mila Nikolova
    • 2
  • Nicolas Papadakis
    • 3
  1. 1.University of BordeauxTalenceFrance
  2. 2.ENS CachanCachanFrance
  3. 3.University of BordeauxTalenceFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18461-6
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-18460-9
  • Online ISBN 978-3-319-18461-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book