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Inverse Scale Space Theory for Inverse Problems

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Part of the book series: Lecture Notes in Computer Science 2106 ((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.

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References

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© 2001 Springer-Verlag Berlin Heidelberg

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Scherzer, O., Groetsch, C. (2001). Inverse Scale Space Theory for Inverse Problems. In: Kerckhove, M. (eds) Scale-Space and Morphology in Computer Vision. Scale-Space 2001. Lecture Notes in Computer Science 2106, vol 2106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47778-0_29

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  • DOI: https://doi.org/10.1007/3-540-47778-0_29

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42317-1

  • Online ISBN: 978-3-540-47778-5

  • eBook Packages: Springer Book Archive

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