Journal Articles

2018

  1. H. Mansour, D. Liu, U. S. Kamilov, and P. T. Boufounos, “Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging,” IEEE Trans. Comput. Imag., vol. 4, no. 4, pp. 537-551, December 2018.
    [doi:10.1109/tci.2018.2875375][arXiv:1805.03269]
  2. E. Bostan, U. S. Kamilov, and L. Waller, “Learning-based Image Reconstruction via Parallel Proximal Algorithm,” IEEE Signal Process. Lett., vol. 25, no. 7, pp. 989-993, July 2018.
    [doi:10.1109/lsp.2018.2833812][arXiv:1801.09518]
  3. Y. Sun, Z. Xia, and U. S. Kamilov, “Efficient and accurate inversion of multiple scattering with deep learning,” Opt. Express, vol. 26, no. 11, pp. 14678-14688, May 2018.
    [doi:10.1364/oe.26.014678][arXiv:1803.06594]
  4. H.-Y. Liu, D. Liu, H. Mansour, P. T. Boufounos, L. Waller, and U. S. Kamilov, “SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering,” IEEE Trans. Comput. Imag., vol. 4, no. 1, pp. 73-86, March 2018.
    [doi:10.1109/tci.2017.2764461][arXiv:1705.04281]

2017

  1. U. S. Kamilov, H. Mansour, and B. Wohlberg, “A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems,” IEEE Signal Process. Lett., vol. 24, no. 12, pp. 1872-1876, December 2017.
    [doi:10.1109/lsp.2017.2763583]
  2. U. S. Kamilov and P. T. Boufounos, “Motion-Adaptive Depth Superresolution,” IEEE Trans. Image Process, vol. 26, no. 4, pp. 1723-1731, April 2017.
    [doi:10.1109/tip.2017.2658944]
  3. U. S. Kamilov, “A Parallel Proximal Algorithm for Anisotropic Total Variation Minimization,” IEEE Trans. Image Process., vol. 26, no. 2, pp. 539-548, February 2017.
    [doi:10.1109/tip.2016.2629449]
  4. S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov, “Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization,” IEEE Trans. Inf. Theory., vol. 63, no. 1, pp. 676-697, January 2017.
    [doi:10.1109/tit.2016.2619373] [arXiv:1501.01797]

2016

  1. U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos, “A Recursive Born Approach to Nonlinear Inverse Scattering,” IEEE Signal Process. Lett., vol. 23, no. 8, pp. 1052-1056, August 2016.
    [doi:10.1109/lsp.2016.2579647] [arXiv:1603.03768]
  2. U. S. Kamilov and H. Mansour, “Learning optimal nonlinearities for iterative thresholding algorithms,” IEEE Signal Process. Lett., vol. 23, no. 5, pp. 747–751, May 2016.
    [doi:10.1109/lsp.2016.2548245] [arXiv:1512.04754]
  3. U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, “Optical tomographic image reconstruction based on beam propagation and sparse regularization,” IEEE Trans. Comput. Imag., vol. 2, no. 1, pp. 59–70, March 2016.
    [doi:10.1109/tci.2016.2519261]

2015

  1. U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, 
“Learning Approach to Optical Tomography,” Optica, vol. 2, no. 6, pp. 517–522, June 2015.
    [doi:10.1364/optica.2.000517] [Nature “News and Views”]
  2. U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, D. Psaltis, and M. Unser, “Isotropic inverse-problem approach for two-dimensional phase unwrapping,” J. Opt. Soc. Am. A, vol. 32, no. 6, pp. 1092–1100, June 2015.
    [doi:10.1364/josaa.32.001092] [arXiv:1503.04744]

2014

  1. U. S. Kamilov, E. Bostan, and M. Unser, “Variational Justification of Cycle Spinning for Wavelet-Based Solutions of Inverse Problems,” IEEE Signal Process. Lett., vol. 21, no. 11, pp. 1326–1330, November 2014.
    [doi:10.1109/lsp.2014.2334306]
  2. U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser, “Approximate Message Passing with Consistent Parameter Estimation and Application to Sparse Learning,” IEEE Trans. Inf. Theory, vol. 60, no. 5, pp. 2969–2985, May 2014.
    [doi:10.1109/tit.2014.2309005]

2013

  1. E. Bostan, U. S. Kamilov, M. Nilchian, and M. Unser, “Sparse Stochastic Processes and Discretization of Linear Inverse Problems,” IEEE Trans. Image Process., vol. 22, no. 7, pp. 2699–2710, July 2013.
    [doi:10.1109/tip.2013.2255305]
  2. A. Kazerouni, U. S. Kamilov, E. Bostan, and M. Unser, “Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning,” IEEE Signal Process. Lett., vol. 20, no. 3, pp. 249–252, March 2013.
    [doi:10.1109/lsp.2013.2242061]
  3. A. Amini, U. S. Kamilov, E. Bostan, and M. Unser, “Bayesian Estimation for Continuous-Time Sparse Stochastic Processes,” IEEE Trans. Signal Process., vol. 61, no. 4, pp. 907–920, February 2013.
    [doi:10.1109/tsp.2012.2226446]
  4. U. S. Kamilov, P. Pad, A. Amini, and M. Unser, “MMSE Estimation of Sparse Lévy Processes,” IEEE Trans. Signal Process., vol. 61, no. 10, pp. 137–147, January 2013.
    [doi:10.1109/tsp.2012.2222394]

2012

  1. U. S. Kamilov, V. K. Goyal, and S. Rangan, “Message-Passing De-Quantization with Applications to Compressed Sensing,” IEEE Trans. Signal Process., vol. 60, no. 12, pp. 6270–6281, December 2012.
    [doi:10.1109/tsp.2012.2217334] [arXiv:1105.6368] [IEEE SPS Best Paper Award 2017]
  2. U. S. Kamilov, A. Bourquard, A. Amini, and M. Unser, “One-Bit Measurements with Adaptive Thresholds,” IEEE Signal Process. Lett., vol. 19, no. 10., pp. 607–610, October 2012.
    [doi:10.1109/lsp.2012.2209640]
  3. U. S. Kamilov, E. Bostan, and M. Unser, “Wavelet Shrinkage with Consistent Cycle Spinning Generalizes Total Variation Denoising,” IEEE Signal Process. Lett., vol. 19, no. 4, pp. 187–190, April 2012.
    [doi:10.1109/lsp.2012.2185929]