Regularization by Denoising applied to non-linear traveltime tomography

• Author / Creator

  Ambros Vargas, Andres A

• The solution of an inverse problem such as the traveltime tomography requires a regu-
  larization function that constrains the solution and stabilizes the inversion. A traditional
  regularization method is the one of Tikhonov, which imposes restrictions on the solution
  such a small norm or smoothness. The recently published Regularization by Denoising from
  the signal processing field proposes to take advantage of the existing powerful denoising al-
  gorithms developed for the removal of Gaussian noise to regularize general inverse problems.
  In this work, we explore the application of this novelty technique for the linear and non-
  linear cases of the traveltime tomography problem and offer a comparison of its performance
  against the one from Tikhonov.

• Subjects / Keywords

  • reularization
  • non-linear inverse problem
  • RED
  • tomography
  • inverse problem
  • Non local means
  • total variation
  • Regularization by Denoising

• Graduation date

  Spring 2020

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-zx7v-s156

• License

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