Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging

Thomas Fromenteze, Sana Abid, Cyril Decroze, Okan Yurduseven

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
15 Downloads (Pure)


Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical layer. This paper presents a new reconstruction technique leveraging the sparsity of the signals in the time-domain and decomposition of the sensing matrix by support detection, the size of the computational inverse problem being reduced significantly without compromising the image quality.
Original languageEnglish
JournalSensors (Basel, Switzerland)
Issue number5
Publication statusPublished - 12 May 2018
Externally publishedYes


  • Computational Imaging
  • Sparsity
  • Microwave

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