Image Decomposition: Theory, Numerical Schemes, and Performance Evaluation

Jerome Gilles
11/8/2024
eess.IVcs.CVmath.FA

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Abstract

This paper describes the many image decomposition models that allow to separate structures and textures or structures, textures, and noise. These models combined a total variation approach with different adapted functional spaces such as Besov or Contourlet spaces or a special oscillating function space based on the work of Yves Meyer. We propose a method to evaluate the performance of such algorithms to enhance understanding of the behavior of these models.

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@article{gilles2024image,
  title  = {Image Decomposition: Theory, Numerical Schemes, and Performance Evaluation},
  author = {Jerome Gilles},
  year   = {2024},
  eprint = {2411.05265},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.05265v1}
}

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