Abstract
Terahertz tomography aims for reconstructing the complex refractive index of a specimen, which is illuminated by electromagnetic radiation in the terahertz regime, from measurements of the resulting (total) electric field outside the object. The illuminating radiation is reflected, refracted, and absorbed by the object. In this work, we reconstruct the complex refractive index from tomographic measurements by means of regularization techniques in order to detect defects such as holes, cracks, and other inclusions, or to identify different materials and the moisture content. Mathematically, we are dealing with a nonlinear parameter identification problem for the two-dimensional Helmholtz equation, and solve it with the Landweber method and sequential subspace optimization. The article concludes with some numerical experiments.
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Acknowledgements
The authors are indebted to Heiko Hoffmann for valuable discussions about the proof of Theorem 2.
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Wald, A., Schuster, T. (2018). Tomographic Terahertz Imaging Using Sequential Subspace Optimization. In: Hofmann, B., Leitão, A., Zubelli, J. (eds) New Trends in Parameter Identification for Mathematical Models. Trends in Mathematics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-70824-9_14
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DOI: https://doi.org/10.1007/978-3-319-70824-9_14
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