Level Set Methods for Structural Inversion and Image Reconstruction

Oliver Dorn () and Dominique Lesselier ()
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Oliver Dorn: The University of Manchester, School of Mathematics
Dominique Lesselier: CNRS, Laboratoire des Signaux et Systemes

A chapter in Handbook of Mathematical Methods in Imaging, 2015, pp 471-532 from Springer

Abstract: Abstract In this chapter, an introduction is given into the use of level set techniques for inverse problems and image reconstruction. Several approaches are presented which have been developed and proposed in the literature since the publication of the original (and seminal) paper by F. Santosa in 1996 on this topic. The emphasis of this chapter, however, is not so much on providing an exhaustive overview of all ideas developed so far but on the goal of outlining the general idea of structural inversion by level sets, which means the reconstruction of complicated images with interfaces from indirectly measured data. As case studies, recent results (in 2D) from microwave breast screening, history matching in reservoir engineering, and crack detection are presented in order to demonstrate the general ideas outlined in this chapter on practically relevant and instructive examples. Various references and suggestions for further research are given as well.

Keywords: History Matching; Mumford Shah Functional; Shape Derivative; Topological Derivatives; Material Derivative Method (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4939-0790-8_11

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DOI: 10.1007/978-1-4939-0790-8_11

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