TR2018-056

SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering


    •  Liu, H.-Y., Liu, D., Mansour, H., Boufounos, P.T., Waller, L., Kamilov, U., "SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering", IEEE Transactions on Computational Imaging, DOI: 10.1109/​TCI.2017.2764461, Vol. 4, No. 1, pp. 73-86, July 9, 2018.
      BibTeX TR2018-056 PDF
      • @article{Liu2018jul,
      • author = {Liu, Hsiou-Yuan and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Waller, Laura and Kamilov, Ulugbek},
      • title = {SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering},
      • journal = {IEEE Transactions on Computational Imaging},
      • year = 2018,
      • volume = 4,
      • number = 1,
      • pages = {73--86},
      • month = jul,
      • doi = {10.1109/TCI.2017.2764461},
      • url = {https://www.merl.com/publications/TR2018-056}
      • }
  • MERL Contacts:
  • Research Area:

    Computational Sensing

Abstract:

Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we describe a new technique called Series Expansion with Accelerated Gradient Descent on Lippmann-Schwinger Equation (SEAGLE) for robust imaging under multiple scattering based on a combination of an iterative forward model and a total variation (TV) regularizer. The proposed method can account for multiple scattering, which makes it advantageous in applications where single scattering approximations are inaccurate. Specifically, the method relies on a series expansion of the scattered wave with an accelerated-gradient method. This expansion guarantees the convergence of the forward model even for strongly scattering objects. One of our key insights is that it is possible to obtain an explicit formula for computing the gradient of an iterative forward model with respect to the unknown object, thus enabling fast image reconstruction with the state-of-the-art fast iterative shrinkage/thresholding algorithm (FISTA). The proposed method is validated on diffraction tomography where complex electric field is captured at different illumination angles.

 

  • Related Publications

  •  Liu, H.-Y., Liu, D., Mansour, H., Boufounos, P.T., Waller, L., Kamilov, U., "SEAGLE: Robust Computational Imaging under Multiple Scattering", OSA Imaging and Applied Optics Congress, DOI: 10.1364/​MATH.2017.MM4C.1, June 2017.
    BibTeX TR2017-081 PDF
    • @article{Liu2017jun,
    • author = {Liu, Hsiou-Yuan and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Waller, Laura and Kamilov, Ulugbek},
    • title = {SEAGLE: Robust Computational Imaging under Multiple Scattering},
    • journal = {OSA Imaging and Applied Optics Congress},
    • year = 2017,
    • month = jun,
    • doi = {10.1364/MATH.2017.MM4C.1},
    • url = {https://www.merl.com/publications/TR2017-081}
    • }
  •  Liu, H.-Y., Liu, D., Mansour, H., Boufounos, P.T., Waller, L., Kamilov, U., "SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering", arXiv, May 2017.
    BibTeX arXiv
    • @article{Liu2017may,
    • author = {Liu, Hsiou-Yuan and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Waller, Laura and Kamilov, Ulugbek},
    • title = {SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering},
    • journal = {arXiv},
    • year = 2017,
    • month = may,
    • url = {https://arxiv.org/abs/1705.04281}
    • }