directory

Yoram Bresler

Yoram Bresler
(217) 244-9660
112 Coordinated Science Lab
Professor
(217) 244-9660
112 Coordinated Science Lab

Research Topics

  • Bioimaging at Multi-Scale

Education

  • Ph.D., Electrical Engineering, Stanford University, 1986

Academic Positions

  • Professor, Electrical & Computer Engineering - August 1997 - Present
  • Research Professor, Coordinated Science Laboratory - August 1997 - Present
  • Professor, Bioengineering, August 1997 - Present (0%)
  • Institute Affiliate, Beckman Institute, 1994 to Present

For more information

Research Topics

  • Bioimaging at Multi-Scale

Research Interests

  • Biomedical imaging systems, inverse problems, compressed sensing, sparse representations, machine learning, big data, Statistical signal and image processing

Research Statement

My current research addresses five main areas:

1) Practical Compressive Sensing. This work addresses the development of theory and methods for sampling signals at less than the Nyquist rate, by using sparsity properties of their representation with respect to an appropriate basis, or in an appropriate space. Applications are being developed in magnetic resonance imaging (MRI) and in computed tomography (CT).

2)Statistical and Machine Learning for Sparse Signal Representation and Compressive Sensing. New methods of learning efficient signal representations from data are being developed and applied to compressive sensing. Learning the models from the sensed data itself provides substantial reduction in the amount of data needed for high-quality reconstruction. The application to Big Data is a recent area of emphasis in this work, which now addresses the development of scalable and on-line algorithms.

3) Statistical and Machine Learning (including deep neural networks) for inverse problems in imaging.

4) Study of fundamental performance bounds and the development of computationally efficient algorithms with provable guaranteed performance for bilinear inverse problems with sparsity constraints. These problems are more difficult than linear inverse problems, and much less is known about their theory. Yet, they arise in many engineering and scientific applications, including the classical problem of blind deconvolution.

5) Signal processing for Big Data, and in particular for mutlidimensional (tensor) data, with applications in brain imaging and neuroscience.

Articles in Conference Proceedings

  • B. Wen, Y. Li, L. Pfister, and Y. Bresler, "Joint Adaptive Sparsity and Low-rankness on the Fly: an Online Tensor Reconstruction Scheme for Video Denoising". In: 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, Oct. 2017, pp. 241-250. doi: 10.1109/ICCV.2017.35.
  • B. Wen, Y Li, and Y. Bresler. "When sparsity meets low-rank: transform learning with non-local low-rank constraint for image restoration". Proc. IEEE int. Conf. Acoust. Speech Sig. Proc. New Orleans, LA, Mar. 2017, pp. 2297-2301. doi: 10.1109/ICASSP.2017.7952566.
  • L. Pfister and Y. Bresler. "Automatic parameter tuning for image denoising with learned sparsifying transforms". In: Proc. IEEE int. Conf. Acoust. Speech Sig. Proc. New Orleans, LA, Mar. 2017, pp. 6040-6044. doi: 10.1109/ICASSP.2017.7953316.
  • Y. Li, K. Lee, and Y. Bresler. "Blind gain and phase calibration for low-dimensional or sparse signal sensing via power iteration". 2017 International Conference on Sampling Theory and Applications (SampTA), Tallin, Estonia, July 2017, pp. 119-123. doi: 10.1109/SAMPTA.2017.8024422.
  • Luke Pfister et al. "Inverse Scattering with Chemical Composition Constraints for Spectroscopic Tomography". Technical Digest Imaging and Applied Optics 2016. Heidelberg, Germany: Optical Society of America, July 2016, pp. MW2I.3. doi: 10.1364/math.2016.mw2i.3
  • B. Sharif and Y. Bresler, ”Distortion-optimal self-calibrating parallel MRI by blind interpolation in subsampled filter banks,” in Proc. 2011 IEEE Int.Symp. Biomedical Imaging (ISBI-2011), Chicago, March 2011.
  • J. Brokish, D.B. Keesing, and Y. Bresler, "Iterative circular conebeam CT reconstruction using fast hierarchical backprojection/reprojection operators", Medical Imaging 2010: Physics of Medical Imaging, Ehsan Samei; Norbert J. Pelc, Editors, Proceedings of SPIE Vol. 7622, pp. 76221R-76221R-9, March 2010. DOI: 10.1117/12.844026.
  • J. Brokish, P. Sack, and Y. bresler, "Combined algorithmic and GPU acceleration for ultra-fast circular conebeam backprojection", Medical Imaging 2010: Physics of Medical Imaging, Ehsan Samei; Norbert J. Pelc, Editors, Proceedings of SPIE Vol. 7622, pp. 762256-762256-9, March 2010. DOI: 10.1117/12.844028
  • B. Sharif, J. A. Derbyshire, and Y. Bresler, "Prospective SNR optimization in k-t-based sensitivity-encoded dynamic imaging using a fast geometric algorithm," in Proc. Int. Symp. Magn. Reson. in Med. ISMRM-2009, Honoloulu, p. 2729, May 2009.
  • B. Sharif, J. A. Derbyshire, A. Z. Farnesh, R. J. Lederman, and Y. Bresler, "Real-time shallow-breathing cardiac MRI using patient-adaptive parallel imaging," in Proc. Int. Symp. Magn. Reson. in Med. ISMRM-2009, Honoloulu, p. 4568, May 2009.
  • Y.Bresler, "Spectrum Blind Sampling and Compressive Sensing," Proc. IEEE Workshop on Information Theory and Applications ITA, pp. 547 -554, Jan. 2008.

Selected Articles in Journals

  • K.Lee, Y. Wu, and Y. Bresler. Near Optimal Compressed Sensing of a Class of Sparse Low-Rank Matrices via Sparse Power Factorization". IEEE Transactions on Information Theory 63.3 (2018), pp. 1666 -1698. doi: 10.1109/TIT.2017.2784479.
  • B. Wen, S. Ravishankar, and Y. Bresler. FRIST - Flipping and Rotation Invariant Sparsifying Transform Learning and Applications," Inverse Problems 33.7 (2017), p. 074007. doi:10.1088/1361-6420/aa6c6e
  • Y. Li, K. Lee, and Y.Bresler. Identifiability and stability in blind deconvolution under minimal assumptions". IEEE Transactions on Information Theory, (2017). Date of Publication: March 30, 2017. doi: 10.1109/TIT.2017.2689779.
  • Y. Li, K. Lee, and Y Bresler. "Identifiability in bilinear inverse problems with applications to Subspace or Sparsity-Constrained Blind Gain and Phase Calibration". In: IEEE Transactions on Information Theory Vol. 63 No. 2 (Feb. 2017), pp. 822-842. Date of Publication: 09 December 2016, doi: 10.1109/TIT.2016.2637933.
  • K. Lee, Y. Li, M. Junge, and Y. Bresler, Blind recovery of sparse signals from subsampled convolution". In: IEEE Transactions on Information Theory Vol. 63 No. 2 (Feb. 2017), pp. 802-821. Date of Publication: 06 December 2016. doi: 10.1109/TIT.2016.2636204.
  • S Ravishankar and Y Bresler. "Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing". In: IEEE Transactions on Computational Imaging Vol. 2 No. 3 (Sept. 2016), pp. 294-309. doi: 10.1109/TCI.2016.2567299.
  • Y. Li, K. Lee, and Y Bresler.Optimal sample complexity for blind gain and phase calibration". In: IEEE Transactions on Signal Processing Vol. 64 (Aug. 2016) pp. 5549-5556. doi: 10.1109/TSP.2016.2598311.
  • Y. Li, K. Lee, and Y Bresler. Identifiability in blind deconvolution with subspace or sparsity constraints". In: IEEE Transactions on Information Theory Vol. 62 No. 7 (July 2016), pp. 4266-4275. doi: 10.1109/TIT.2016.2569578.
  • S Ravishankar and Y Bresler. Efficient blind compressed sensing using sparsifying transforms with convergence guarantees and application to magnetic resonance imaging". In: SIAM Journal on Imaging Sciences Vol. 8 No.4 (2015), pp. 2519-2557. doi: 10.1137/141002293.
  • S. Ravishankar and Y. Bresler, "Online Sparsifying Transform Learning - Part II: Convergence Analysis " IEEE Journal on Selected Topics in Signal Processing, Special Issue on Big Data, 2015, DOI: 10.1109/JSTSP.2015.2407860 .
  • S. Ravishankar, B. Wen, and Y. Bresler, "Online Sparsifying Transform Learning - Part I: Algorithms" IEEE Journal on Selected Topics in Signal Processing, Special Issue on Big Data, 2015, DOI: 10.1109/JSTSP.2015.2417131.
  • S. Ravishankar, and Y. Bresler, "$\ell_0$ Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees," IEEE Transactions on Signal Processing, 2015, DOI: 10.1109/TSP.2015.2405503.
  • B. Wen, S. Ravishankar, and Y. Bresler, "Structured overcomplete sparsifying transform learning with convergence guarantees and applications," International Journal of Computer Vision, Vol. 114 No. 2-3, September 2015, pp. 137-167. DOI 10.1007/s11263-014-0761-1
  • (*)(W) S. Ravishankar and Y. Bresler, “Learning doubly sparse transforms for images,” IEEE Trans Image Process. 2013 Dec; v 22 n. 12, pp. 4598-612. doi: 10.1109/TIP.2013.2274384.
  • K. Lee, Y. Bresler, and M. Junge, "Oblique Pursuits for Compressed Sensing,", IEEE Trans. Information Theory, v 59 n 9, pp. 6111-6141, 2013.
  • A. K. George and Y. Bresler, "A fast fan-beam backprojection algorithm based on efficient sampling," Physics in Medicine and Biology, v 58, n 5, p 1415-31, 7 March 2013
  • S. Ravishankar and Y. Bresler, "Learning Sparsifying Transforms," IEEE Transactions on Signal Processing, v 61, n 5, p 1072-86, 1 March 2013
  • K. Lee, Y. Bresler, and M. Junge, "Subspace Methods for Joint Sparse Recovery,"  IEEE Trans. Information Theory, v 58, n 6, p 3613-41, June 2012
  • B. Sharif and Y. Bresler, "Generic Feasibility of Perfect Reconstruction with Short FIR Filters in Multi-channel Systems," IEEE Trans. Signal Processing, Vol. 59, No. 11, DOI: 10.1109/TSP.2011.2166550, Dec. 2011
  • G. Wang, Y. Bresler, and V. Ntziachristos, "Guest Editorial: Compressive Sensing for Biomedical Imaging," IEEE Trans. Med. Imag., vol. 30, no. 5, pp. 1013-1016, May 2011.
  • O. Lee, J. Kim, Y. Bresler, and J. C. Ye, "Compressive diffuse optical tomography: Non-iterative exact reconstruction using joint sparsity," IEEE Trans. Med. Imag., vol. 30, no. 5, May 2011.
  • S. Ravishankar and Y. Bresler, ”MR Image Reconstruction From Highly Undersampled k-space Data by Dictionary Learning,” IEEE Tans. Medical Imaging, Spec. Issue Compressive Sensing, vol. 30, no. 5, May 2011.
  • K. Lee and Y. Bresler, "ADMiRA: Atomic Decomposition for Minimum Rank Approximation", IEEE Transactions on Information Theory, vol. 56, No. 9, Sep. 2010.
  • B. Sharif, J. A. Derbyshire, A. Z. Faranesh, and Y. Bresler, "Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE),'' Magnetic Resonance in Medicine,MRM, vol. 64 No. 2, pp. 501-513, 2010.
  • N. Aggarwal and Y. Bresler, "Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI," Inverse Problems, vol. 24, no. 4, pp. 045015-1 - 045015-29, 2008.
  • A.K. George and Y. Bresler, ``Fast tomographic reconstruction via rotation-based hierarchical backprojection,'' SIAM J. Appl.Math, vol.68, pp. 574 - 589, Dec. 2007
  • A.K. George and Y. Bresler, "Shear-based Fast Hierarchical Backprojection for Parallel-Beam Tomography," IEEE Transactions on Medical Imaging, Vol. 26 No. 3, pp. 317-334, March 2007.
  • M. Jacob, Y. Bresler, V. Toronov, X. Zhang, and A. Webb, "A level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging", J. Biomedical Optics, Vol. 11, No. 6, 064029, Nov. 2006.
  • J.C. Ye, P. Moulin, and Y.Bresler, ``Asymptotic global confidence regions for 3-D parametric shape estimation in inverse problems,'' IEEE Trans. Image Processing, v. 15, n 10, pp. 2904-2919, Oct. 2006.
  • D. Baron and Y.Bresler, ``Antisequential suffix sorting for BWT-based data compression,'' IEEE Trans. Computers, vol. 54, no. 4, pp. 385-397, Apr. 2005.
  • D. Baron and Y. Bresler, "O(N) Semi-Predictive Universal Encoder via the BWT." IEEE Transactions on Information Theory, Vol. 50 , No. 5 , pp. 928 - 937, May 2004.
  • R. Venkataramani and Y. Bresler, "Multiple-input multiple-output sampling: Necessary density conditions," IEEE Transactions on Information Theory, vol. 50, pp. 1754-1768, Aug. 2004.
  • R. Venkataramani and Y. Bresler, "Filter Design for MIMO Sampling and Reconstruction," IEEE Transactions on Signal Processing, vol. 51, no. 12, pp. 3164-3176, December 2003.
  • R. Venkataramani and Y. Bresler, "Sampling Theorems for Uniform and Periodic Nonuniform MIMO Sampling of Multiband Signals," IEEE Transactions on Signal Processing, vol. 51, no. 12, pp. 3152-3163, December 2003.
  • J. C. Ye, Y. Bresler, and P. Moulin, "Cramer-Rao bounds for parametric shape estimation in inverse problems," IEEE Transactions on Image Processing, no. 1, pp. 71-84, January 2003.
  • M. C. Robini, Y. Bresler, and I. E. Magnin, "On the convergence of Metropolis-type relaxation and annealing with constraints," Probability in the Engineering Informational Sciences, vol. 16, no. 4, pp. 427-452, 2002.
  • S. Levy, D. Adam, and Y. Bresler, "Electromagnetic impedance tomography (EMIT): a new method for impedance imaging," IEEE Transactions on Medical Imaging, vol. 21, no. 6, pp. 676-687, June 2002.
  • J. C. Ye, Y. Bresler, and P. Moulin, "A self-referencing level-set method for image reconstruction from sparse Fourier samples," International Journal of Computer Vision, vol. 50, no. 3, pp. 253-70, December 2002.
  • S. Basu and Y. Bresler, "An empirical study of minimax-optimal fractional delays for lowpass signals," IEEE Transactions on Circuits Systems II, vol. 49, no. 4, pp. 288-292, April 2002.
  • S. Basu and Y. Bresler, "O(N^3 log N) backprojection algorithm for the 3D Radon transform," IEEE Transactions on Medical Imaging, vol. 21, no. 2, pp. 76-88, February 2002.
  • R. Venkataramani and Y. Bresler, "Optimal sub-Nyquist nonuniform sampling and reconstruction of multiband signals," IEEE Transactions on Signal Processing, vol. 49, no. 10, pp. 2301-2313, October 2001.
  • J. C. Ye, Y. Bresler, and P. Moulin, "Cramer-rao bounds for parametric boundaries of targets in inverse scattering problems," IEEE Transactions on Antennas and Propagation, vol. 49, no. 5, pp. 2301-2313, May 2001.
  • S. Basu and Y. Bresler, "Error analysis and performance optimization in fast hierarchical backprojection algorihtms," IEEE Transactions on Image Processing, vol. 10, no. 7, pp. 1103-1117, July 2001.
  • S. Basu and Y. Bresler, "Stability of nonlinear least-squares problems and the Cramer-Rao bound," IEEE Transactions on Signal Processing, vol. 48, no. 12, pp. 3426-3436, December 2000.
  • S. Basu and Y. Bresler, "An O(n^2 log n) filtered backprojection reconstruction algorithm for tomography," IEEE Transactions on Image Processing, vol. 9, pp. 1760-1773, October 2000.
  • A. Boag, Y. Besler, and E. Michielssen, "A multilvel domain decomposition algorithm for fast O(n^2\log n) reprojection of tomographic images," IEEE Transactions on Image Processing, vol. 9, pp. 1573-1582, September 2000.
  • R. Venkataramani and Y. Bresler, "Perfect reconstruction formulae and bounds on aliasing error in sub-Nyquist sampling of multiband signals," IEEE Transactions on Information Theory, vol. 46, no. 6, pp. 2173-83, September 2000.
  • J. C. Ye, Y. Bresler, and P. Moulin, "Global confidence regions in parametric shape estimation problems," IEEE Transactions on Information Theory, vol. 46, no. 5, pp. 1881-1895, August 2000.
  • S. K. Basu and Y. Bresler, "Feasibility of tomography with unknown view angles," IEEE Transactions on Image Processing, vol. 9, pp. 1106-1122, June 2000.
  • S. K. Basu and Y. Bresler, "Uniqueness of tomography with unknown view angles," IEEE Transactions on Image Processing, vol. 9, pp. 1094-1106, June 2000.
  • S. K. Basu and Y. Bresler, "A global lower bound on parameter estimation error with periodic distortion functions," IEEE Transactions on Information Theory, vol. 46, pp. 1145-1150, May 2000.
  • S.-F. Yau and Y. Bresler, "Performance analysis of the approximate dynamic programming algorithm for parameter estimation of superimposed signals," IEEE Transactions on Signal Processing, vol. 48, pp. 1274-1286, May 2000. 2000.
  • C. Couvreur and Y. Bresler, "On the optimality of the backward greedy algorithm for the subset selection problem," SIAM Journal of Matrix Analysis and Applications, vol. 21, no. 3, pp. 797-808, 2000. Doi: 0.1137/S0895479898332928
  • G. Harikumar and Y. Bresler, "Exact image deconvolution from multiple {FIR} blurs," IEEE Transactions on Image Processing, vol. 8, pp. 846-862, June 1999.
  • I. B. Kerfoot and Y. Bresler, "Theoretical analysis of multichannel MRF image segmentation algorithms," IEEE Transactions on Image Processing, vol. 8, pp. 798-820, June 1999.
  • G. Harikumar and Y. Bresler, "Blind restoration of images blurred by multiple filters: theory and efficient algorithms," IEEE Transactions on Image Processing, vol. 8, pp. 202-219, February 1999.
  • C. Couvreur and Y. Bresler, "Automatic classification of environment noise sources by statistical methods," Noise Control Engineering Journal, vol. 46, no. 4, pp. 1-16, July-August 1998
  • A. H. Delaney and Y. Bresler, "Globally convergent edge-preserving regularized reconstruction: an application to limited-angle tomography," IEEE Transactions on Image Processing, pp. 204-221, February 1998.
  • G. Harikumar and Y. Bresler, "FIR perfect signal reconstruction from multiple convolutions: Minimum deconvolver orders," IEEE Transactions on Signal Processing, pp. 215-218, January 1998.
  • Lee M. Garth and Y. Bresler, "Degradation of higher order detection using narrowband processing," IEEE Transactions on Signal Processing, pp. 1770-1784, July 1997.
  • N. P. Willis and Y. Bresler, "Lattice-theoretic analysis of time-sequential sampling of spatio-temporal signals, Part II: Large space-bandwidth-product asymptotics," IEEE Transactions on Information Theory, pp. 208-220, January 1997.
  • N. P. Willis and Y. Bresler, "Lattice-theoretic analysis of time-sequential sampling of spatio-temporal signals, Part I," IEEE Transactions on Information Theory, pp. 190-207, January 1997.
  • Y. Bresler, "Bounds on the aliasing error in multidimensional shannon sampling," IEEE Transactions on Information Theory, pp. 2238-2241, November 1996.
  • S. F. Yau and Y. Bresler, "On the robustness of parameter estimation of superimposed signals by dynamic programming," IEEE Transactions on Signal Processing, pp. 2825-2836, November 1996.
  • G. Harikumar and Y. Bresler, "Feature extraction techniques for exploratory visualization of vector-valued imagery," IEEE Transacations on Image Processing, pp. 1324-1334, September 1996.
  • L. M. Garth and Y. Bresler, "On the use of asymptotics in detection and estimation," IEEE Transactions on Signal Processing, pp. 1304-1307, May 1996.
  • L. M. Garth and Y. Bresler, "A comparison of optimized higher-order detection techniques for non-gaussian signals," pp. 1198-1213, May 1996.
  • A. H. Delaney and Y. Bresler, "A fast and accurate iterative reconstruction algorithm for parallel-beam tomography," IEEE Transactions on Image Processing, pp. 740-753, May 1996.
  • A. H. Delaney and Y. Bresler, "Multiresolution tomographic reconstruction using wavelets," IEEE Transactions on Image Processing, pp. 799-814, June 1995.
  • N. P. Willis and Y. Bresler, "Optimal scan design for time varying tomographic imaging {II}: Efficient design and experimental validation," IEEE Transactions on Image Processing, pp. 654-666, May 1995.
  • N. P. Willis and Y. Bresler, "Optimal scan design for time varying tomographic imaging {I}: Theoretical analysis and fundamental limitations," IEEE Transactions on Image Processing, pp. 642-653, May 1995.
  • T. D. Raymund, Y. Bresler, and R. E. Daniell, "Model-assisted ionospheric tomography: A new algorithm," Radio Science, vol. 29, pp. 1493-1512, November 1, 1994.
  • S. F. Yau and Y. Bresler, "Maximum likelihood parameter estimation of superimposed signals by dynamic programming," IEEE Transaactions on Signal Processing, pp. 804-820, February 1993.
  • S. F. Yau and Y. Bresler, "Maximum likelihood parameter estimation and subspace fitting of superimposed signals by dynamic programming - An approximate method," Signal Processing, vol. 29, pp. 283-298, December 1992.
  • S. F. Yau and Y. Bresler, "Worst-case Cramer-Rao bounds for parametric estimation of superimposed signals," IEEE Transactions on Signal Processing, pp. 2973-2986, December 1992.
  • S. F. Yau and Y. Bresler, "A compact Cramer-Rao bound expression for parametric estimation of superimposed signals," IEEE Transactions on Signal Processing, pp. 1226-1230, May 1992.
  • N. P. Willis and Y. Bresler, "Norm invariance of minimax-optimal interpolation," IEEE Trans. Infor. Theory, pp. 1177-1181 May 1992 .
  • S. F. Yau and Y. Bresler, "A generalization of Bergstorm's inequality and some applications," Linear Algebra and Applications, pp. 135-151, 1992.
  • Y. Bresler, J. A. Fessler, and A. Macovski, "A Bayesian Approach to Reconstruction from Incomplete Projections of a Multiple Object 3D Domain," IEEE Transactions on Pattern Recognition and Machine Intelligence, pp. 840-858, August 1989.
  • Y. Bresler, J. A. Fessler, and A. Macovski, "Model Based Estimation Techniques for 3-D Reconstruction from Projections," Machine Vision and Applications, vol. 1, no. 2, pp. 115-126, 1988.
  • Y. Bresler and T. Kailath, "Model Based Tracking of Signal Shift and Shape," in joint special issue of Automatique Productique Informatique Industrielle (AFCET) and Traitment du Signal (GRETSI), vol. APII 22, no. 3, pp. 269-291, 1988.
  • Y. Bresler, V. U. Reddy, and T. Kailath, "Optimum Beamforming for Coherent Signal and Interferences," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-36, pp. 833 - 843, June 1988.
  • Y. Bresler and A. Macovski, "3-D reconstruction from projections with incomplete and noisy data by object estimation," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-35, pp. 1139-1152, August 1987.
  • Y. Bresler and S. J. Merhav, "Recursive image registration with applications to motion estimation," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-35, pp. 70-85, January 1987.
  • Y. Bresler and A. Macovski, "On the number signals resolvable by a uniform linear array," IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP, vol. ASSP-34, pp. 1361-1375, December 1986.
  • Y. Bresler and A. Macovski, "Exact maximum likelihood parameter estimation of superimposed exponential signals in noise," IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP, vol. ASSP-34, pp. 1081-1089, October 1986.
  • Y. Bresler and S. J. Merhav, "On-line vehicle motion estimation from visual terrain information Part II: Ground velocity and position estimation," IEEE Transactions on Aerospace and Electronic Systems, vol. AES-22, pp. 588-603, September 1986.
  • S. J. Merhav and Y. Bresler, "On-line vehicle motion estimation from visual terrain information Part I: Recursive image registration," IEEE Transactions on Aerospace and Electronic Systems, vol. AES-22, pp. 583-587, September 1986.
  • Y. Bresler, "Two filter formulae for Bayesian smoothing," International Journal of Control, vol. 43, pp. 629-641, 1986.

Journal Editorships

  • Guest Editor, IEEE Trans. on Medical Imaging, Special Issue on Compressed Sensing 2011
  • Member Editorial Board, Society for Industrial and Applied Mathematics, Journal on Imaging Sciences 2007- 2013
  • Member Senior Editorial Board, Journal on Special Topics in Signal Processing, 2006- 2013
  • 1991-1993: Associate Editor, IEEE Transactions on Image Processing.
  • 1987-2005: Associate Editor, Machine Vision and Application: An International Journal.

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