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Inverse Scale Space Theory for Inverse Problems

  • Otmar Scherzer
  • Chuck Groetsch
Conference paper
Part of the Lecture Notes in Computer Science 2106 book series (LNCS, volume 2106)

Abstract

In this paper we derive scale space methods for inverse problems which satisfy the fundamental axioms of fidelity and causality and we provide numerical illustrations of the use of such methods in deblurring. These scale space methods are asymptotic formulations of the Tikhonov-Morozov regularization method. The analysis and illustrations relate difusion filtering methods in image processing to Tikhonov regularization methods in inverse theory.

Keywords

Inverse Problem Regularization Method Scale Space Tikhonov Regularization Fundamental Axiom 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Otmar Scherzer
    • 1
  • Chuck Groetsch
    • 2
  1. 1.Angewandte MathematikUniversität BayreuthBayreuthGermany
  2. 2.Department of MathematicsUniversity of CincinnatiOhioUSA

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