Variational Regularization for Systems of Inverse Problems: Tikhonov Regularization with Multiple Forward Operators

ISBN-13: 9783658253899 / Angielski / Miękka / 2019 / 136 str.

Richard Huber

Spis treści

General Tikhonov Regularization.- Specific Discrepancies.- Regularization Functionals.- Application to STEM Tomography Reconstruction.

O autorze

Richard Huber wrote his master’s thesis under the supervision of Prof. Dr. Kristian Bredies at the Institute for Mathematics and Scientific Computing at Graz University, Austria.

Blurb

Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scientific fields. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their specific structure. Such an approach allows to choose the regularization weights of each subproblem individually with respect to the corresponding noise levels and degrees of ill-posedness.

Contents

• General Tikhonov Regularization
  
• Specific Discrepancies
  
• Regularization Functionals
  
• Application to STEM Tomography Reconstruction
  

Target Groups

• Researchers and students in the field of mathematics
  
• Experts in the areas of mathematics, imaging, computer vision and nanotechnology
  

The Author
Richard Huber wrote his master’s thesis under the supervision of Prof. Dr. Kristian Bredies at the Institute for Mathematics and Scientific Computing at Graz University, Austria.