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Quantitative microwave imaging based on a huber regularization

Funing Bai (UGent) , Wilfried Philips (UGent) and Aleksandra Pizurica (UGent)
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Abstract
Reconstruction of inhomogeneous dielectric objects from microwave scattering by means of quantitative microwave tomography is a nonlinear, ill-posed inverse problem. In this paper, we employ the Huber function as a robust regularization approach for this challenging problem. The resulting reconstructions both in 2D and 3D from sparse data points for piecewise constant objects are encouraging. The reconstructions of more complex permittivity profiles from breast phantom data indicate potential for use in biomedical imaging.
Keywords
inverse problem, Huber regularization, robust estimation, microwave imaging

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Please use this url to cite or link to this publication:

Chicago
Bai, Funing, Wilfried Philips, and Aleksandra Pizurica. 2013. “Quantitative Microwave Imaging Based on a Huber Regularization.” In IEICE Information and Communication Technology Forum, Proceedings.
APA
Bai, F., Philips, W., & Pizurica, A. (2013). Quantitative microwave imaging based on a huber regularization. IEICE Information and Communication Technology Forum, Proceedings. Presented at the IEICE Information and Communication Technology Forum (ICTF - 2013).
Vancouver
1.
Bai F, Philips W, Pizurica A. Quantitative microwave imaging based on a huber regularization. IEICE Information and Communication Technology Forum, Proceedings. 2013.
MLA
Bai, Funing, Wilfried Philips, and Aleksandra Pizurica. “Quantitative Microwave Imaging Based on a Huber Regularization.” IEICE Information and Communication Technology Forum, Proceedings. 2013. Print.
@inproceedings{3178226,
  abstract     = {Reconstruction of inhomogeneous dielectric objects from microwave scattering by means of quantitative microwave tomography is a nonlinear, ill-posed inverse problem. In this paper, we employ the Huber function as a robust regularization approach for this challenging problem. The resulting reconstructions both in 2D and 3D from sparse data points for piecewise constant objects are encouraging. The reconstructions of more complex permittivity profiles from breast phantom data indicate potential for use in biomedical imaging.},
  author       = {Bai, Funing and Philips, Wilfried and Pizurica, Aleksandra},
  booktitle    = {IEICE Information and Communication Technology Forum, Proceedings},
  language     = {eng},
  location     = {Sarajevo, Bosnia and Herzegovina},
  pages        = {6},
  title        = {Quantitative microwave imaging based on a huber regularization},
  year         = {2013},
}