Introducing Maximal Anisotropy into Second Order Coupling Models

  • David Hafner
  • Christopher Schroers
  • Joachim Weickert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9358)

Abstract

On the one hand, anisotropic diffusion is a well-established concept that has improved numerous computer vision approaches by permitting direction-dependent smoothing. On the other hand, recent applications have uncovered the importance of second order regularisation. The goal of this work is to combine the benefits of both worlds. To this end, we propose a second order regulariser that allows to penalise both jumps and kinks in a direction-dependent way. We start with an isotropic coupling model, and systematically introduce anisotropic concepts from first order approaches. We demonstrate the benefits of our model by experiments, and apply it to improve an existing focus fusion method.

Notes

Acknowledgments

Our research has been partially funded by the Deutsche Forschungsgemeinschaft (DFG) through a Gottfried Wilhelm Leibniz Prize for Joachim Weickert. This is gratefully acknowledged.

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Copyright information

© Springer International Publishing Switzerland 2015

Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • David Hafner
    • 1
  • Christopher Schroers
    • 1
  • Joachim Weickert
    • 1
  1. 1.Mathematical Image Analysis Group, Faculty of Mathematics and Computer ScienceSaarland UniversitySaarbrückenGermany

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