TR2017-009

Compressive Imaging with Iterative Forward Models

    •  Liu, H.-Y., Kamilov, U., Liu, D., Mansour, H., Boufounos, P.T., "Compressive Imaging with Iterative Forward Models", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2017.
      BibTeX TR2017-009 PDF
      • @inproceedings{Liu2017mar2,
      • author = {Liu, Hsiou-Yuan and Kamilov, Ulugbek and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T.},
      • title = {Compressive Imaging with Iterative Forward Models},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2017,
      • month = mar,
      • url = {https://www.merl.com/publications/TR2017-009}
      • }
  • MERL Contacts:
  • Research Area:

    Computational Sensing

Abstract:

We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements. Our method relies on a novel, nonlinear measurement model that can account for the multiple scattering phenomenon, which makes the method preferable in applications where linear measurement models are inaccurate. We construct the measurement model by expanding the scattered wave-field with an accelerated-gradient method, which is guaranteed to converge and is suitable for large-scale problems. We provide explicit formulas for computing the gradient of our measurement model with respect to the unknown image, which enables image formation with a sparsity-driven numerical optimization algorithm. We validate the method both analytically and with numerical simulations

 

  • Related News & Events

    •  NEWS    MERL to present 10 papers at ICASSP 2017
      Date: March 5, 2017 - March 9, 2017
      Where: New Orleans
      MERL Contacts: Petros T. Boufounos; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Anthony Vetro; Ye Wang
      Research Areas: Computer Vision, Computational Sensing, Digital Video, Information Security, Speech & Audio
      Brief
      • MERL researchers will presented 10 papers at the upcoming IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), to be held in New Orleans from March 5-9, 2017. Topics to be presented include recent advances in speech recognition and audio processing; graph signal processing; computational imaging; and privacy-preserving data analysis.

        ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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