Sparsity Regularized Nonlinear Inversion for Microwave Imaging

Ulas Taskin*, Ozgur Ozdemir

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

We present a novel microwave imaging technique for sparse domain imaging applications. In the proposed method, inverse scattering algorithm modified gradient method (MGM) is combined with a fast iterative shrinkage-thresholding algorithm to improve the resolution and robustness of the MGM by enforcing the sparsity in the imaging domain. The numerical experiments show that the proposed method achieves higher resolution and robustness compared with that of classical MGM. For nonsparse domain reconstruction, the wavelet transformation is adopted to convert nonsparse spatial domain into a sparse wavelet coefficient domain. The feasibility of the proposed method in the wavelet domain is demonstrated through the numerical experiments.

Original languageEnglish
Article number8067638
Pages (from-to)2220-2224
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume14
Issue number12
DOIs
Publication statusPublished - Dec 2017

Bibliographical note

Publisher Copyright:
© 2004-2012 IEEE.

Keywords

  • Compressive sensing
  • inverse scattering
  • microwave imaging
  • sparsity regularization
  • wavelet transform

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