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Two New Nonlinear Nonlocal Diffusions for Noise Reduction

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Abstract

Two new nonlocal nonlinear diffusion models for noise reduction are proposed, analyzed and implemented. They are both a close relative of the celebrated Perona-Malik equation. In a way, they can be viewed as a new regularization paradigm for Perona-Malik. They do preserve and enhance the most cherished features of Perona-Malik while delivering well-posed equations which admit a stable natural discretization. Unlike other regularizations, however, certain piecewise smooth functions are (meta)stable equilibria and, as a consequence, their dynamical behavior and that of their discrete implementations can be fully understood and do not lead to any “paradox”. The presence of nontrivial equilibria also explains why blurring is kept in check. One of the models has been proved to be well-posed. Numerical experiments are presented that illustrate the main features of the new models and that provide insight into their interesting dynamical behavior as well as demonstrate their effectiveness as a denoising tool.

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Authors and Affiliations

  1. Department of Mathematics, University of California at Irvine, Irvine, CA, 92697-3875, USA

    Patrick Guidotti

  2. Department of Energy Resources Engineering, Stanford University, Stanford, CA, 94305-2220, USA

    James V. Lambers

Authors
  1. Patrick Guidotti
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  2. James V. Lambers
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Correspondence to Patrick Guidotti.

Additional information

This research was supported by the National Science Foundation under award number DMS-0712875.

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Guidotti, P., Lambers, J.V. Two New Nonlinear Nonlocal Diffusions for Noise Reduction. J Math Imaging Vis 33, 25–37 (2009). https://doi.org/10.1007/s10851-008-0108-z

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  • DOI: https://doi.org/10.1007/s10851-008-0108-z

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