3D quantitative microwave imaging from sparsely measured data with Huber regularization

Funing Bai; Aleksandra Pižurica

doi:10.1117/12.2038500

7 March 2014 3D quantitative microwave imaging from sparsely measured data with Huber regularization

Funing Bai, Aleksandra Pižurica

Proceedings Volume 9020, Computational Imaging XII; 90200E (2014) https://doi.org/10.1117/12.2038500
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

Reconstructing complex permittivity profiles of dielectric objects from measurements of the microwave scattered field is a non-linear ill posed inverse problem. We analyze the performance of the Huber regularizer in the application, studying the influence of the parameters under different noise levels. Moreover, we evaluate the whole approach on real 3D electromagnetic measurements. Our focus is on reconstructions from relatively few measurements (sparse measurements) to speed up the reconstruction process.

Citation Download Citation

Funing Bai and Aleksandra Pižurica "3D quantitative microwave imaging from sparsely measured data with Huber regularization", Proc. SPIE 9020, Computational Imaging XII, 90200E (7 March 2014); https://doi.org/10.1117/12.2038500

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KEYWORDS

3D metrology

Microwave imaging

Optical spheres

3D acquisition

Signal to noise ratio

Inverse problems

Reconstruction algorithms

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