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A Multiplicative Regularizer Augmented with Spatial Priors for Microwave Imaging
  • Nozhan Bayat ,
  • Puyan Mojabi
Nozhan Bayat
University of Manitoba, University of Manitoba

Corresponding Author:[email protected]

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Puyan Mojabi
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The standard weighted L2 norm total variation multiplicative regularization (MR) term originally developed for microwave imaging algorithms is modified to take into account
structural prior information, also known as spatial priors (SP), about the object being imaged. This modification adds one extra term to the integrand of the standard MR, thus, being referred to as an augmented MR (AMR). The main advantage of the proposed approach is that it requires a minimal change to the existing microwave imaging algorithms that are already equipped with the MR. Using two experimental data sets, it is shown that the proposed AMR (i) can handle partial SP, and (ii) can, to some extent, enhance the quantitative accuracy achievable from
microwave imaging.
Jan 2021Published in IEEE Transactions on Antennas and Propagation volume 69 issue 1 on pages 606-611. 10.1109/TAP.2020.2998913