Publications

Journal papers

  1. M. Protter and M. Elad " Super-Resolution With Probabilistic Motion Estimation" , Book Chapter in "Super-Resolution Imaging", CRC Press, 2010, Peyman Milanfar (Editor).
  2. J. Shtok, M. Elad, and M. Zibulevsky, " Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning", Submitted to  IEEE Transactions on Medical Imaging. 
  3. M. Elad and M. Zibulevsky, " Iterated Shrinkage Algorithms in Signal and Image Processing", Submitted to  IEEE Signal Processing Magazine. 
  4. Z. Ben-Haim, Y.C. Eldar, and M. Elad, " Near-Oracle Performance of Basis Pursuit under Random Noise", Submitted to  IEEE Transactions on Signal Processing. 
  5. M. Protter, I. Yavneh, and M. Elad, " Closed-Form MMSE Estimation for Signal Denoising Under Sparse Representation Modelling Over a Unitary Dictionary", Submitted to  IEEE Transactions on Signal Processing. 
  6. R. Rubinstein, A.M. Bruckstein, and M. Elad, "Dictionaries for Sparse Representation Modeling", Submitted to  IEEE Proceedings - Special Issue on Applications of Compressive Sensing & Sparse Representation. 
  7. M. Elad, M.A.T. Figueiredo, and Y. Ma, " On the Role of Sparse and Redundant Representations in Image Processing", to appear in the  IEEE Proceedings - Special Issue on Applications of Compressive Sensing & Sparse Representation. 
  8. H. Takeda, P. Milanfar, M. Protter, and M. Elad, "Super-resolution Without Explicit Subpixel Motion Estimation", IEEE Transactions on Image Processing, Vol. 18, No. 9, Pages 1958-1975, September 2009. 
  9. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, "Simultaneous Demosaicking and Resolution Enhancement From Under-Sampled Image Sequences", Book Chapter in "Single-Sensor Imaging: Methods and Applications for Digital Cameras", CRC Press, 2008, Rastislav Lukac (Editor), Pages 503-533.
  10. M. Protter and M. Elad, "Super-Resolution With Probabilistic Motion Estimation", IEEE Transactions on Image Processing, Vol. 18, No. 8, Pages 1899-1904, August 2009.
  11. R. Rubinstein, M. Zibulevsky, and M. Elad, "Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation" , to appear in IEEE Transactions on Signal Processing.
  12. M. Elad and I. Yavneh, "A Plurality of Sparse Representations is Better than the Sparsest One Alone", IEEE Transactions on Information Theory, Vol. 55, No. 10, Pages 4701-4714, October 2009.
  13. M. Protter, M. Elad, H. Takeda, and P. Milanfar, "Generalizing the Non-Local-Means to Super-Resolution Reconstruction", IEEE Transactions on Image Processing, Vol. 18, No. 1, Pages 36-51, January 2009. 
  14. M. Aharon and M. Elad, "Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary", SIAM Journal on Imaging Sciences, Vol. 1, No. 3, pages 228-247, July 2008.
  15. A.M. Bruckstein, M. Elad, and M. Zibulevsky, "A Non-Negative and Sparse Enough Solution of an Underdetermined Linear System of Equations is Unique",    IEEE Transactions on Information Theory, Vol. 54, No. 11, Pages 4813-4820, November 2008.
  16. J. Shtok and M. Elad, "Analysis of the Basis Pursuit Via the Capacity Sets", Journal of Fourier Analysis and Applications, Vol. 14, No. 5-6, Pages: 688-711, December 2008.
  17. M. Protter and Michael Elad, "Image Sequence Denoising Via Sparse and Redundant Representations", IEEE Trans. on Image Processing, Vol. 18, No. 1, Pages 27-36, January 2009.
  18. O. Bryt and M. Elad,"Compression of Facial Images Using the K-SVD Algorithm", Journal of Visual Communication and Image Representation, Vol. 19, No. 4, Pages 270-283, May 2008.
  19. J. Mairal, G. Sapiro, and M. Elad, "Learning Multiscale Sparse Representations for Image and Video Restoration", SIAM Multiscale Modeling and Simulation, Vol. 7, No. 1, pages 214-241, April 2008.
  20. M. Elad, " Optimized Projections for Compressed-Sensing",   IEEE Trans. on Signal Processing, Vol. 55, No. 12, pages 5695-5702, December 2007.
  21. A.M. Bruckstein, D.L. Donoho, and M. Elad, "From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images", SIAM Review, Vol. 51, No. 1, Pages 34-81, February 2009.
  22. C. Staelin, M. Elad, D. Graig, O. Shmueli, and M. Vans, "Biblio – Automatic Meta-data Extraction", International journal on Document Analysis and Recognition, Vol. 10, No. 2, pages 113-126, November 2007.
  23. J. Mairal, M. Elad, and G. Sapiro, "Sparse Representation for Color Image Restoration", IEEE Trans. on Image Processing, Vol. 17, No. 1, pages 53-69, January 2008.
  24. M. Elad, R. Goldenberg, and R. Kimmel, "Low Bit-Rate Compression of Facial Images", IEEE Trans. on Image Processing, Vol. 16, no. 9, pages 2379-2383, September 2007.
  25. D.L. Donoho, M. Elad, and V.N. Temlyakov, "On Lebesgue-Type Inequalities for Greedy Approximation", Journal of Approximation Theory, Vol. 147, No. 2, pages 185-195, August 2007. 
  26. M. Elad, P. Milanfar, and R. Rubinstein, "Analysis Versus Synthesis in Signal Priors", Inverse Problems. Vol. 23, no. 3, pages 947-968, June 2007.
  27. M. Elad, B. Matalon, and M. Zibulevsky, "Coordinate and Subspace Optimization Methods for Linear Least Squares with Non-Quadratic Regularization", Applied and Computational Harmonic Analysis, Vol. 23, pp. 346-367, November 2007.
  28. M. Elad and D. Datsenko, "Example-Based Regularization Deployed to Super-Resolution Reconstruction of a Single Image", The Computer Journal, Vol. 50, no. 4, pages 1-16, April 2007.
  29. D. Datsenko and M. Elad, "Example-Based Single Image Super-Resolution: A Global MAP Approach with Outlier Rejection", Journal of Multidimensional System and Signal Processing, Vol. 18, no. 2-3, pages 103-121, September 2007.
  30. E. Kidron, Y.Y. Schechner, and M. Elad, "Cross-Modality Localization via Sparsity", IEEE Trans. On Signal Processing, Vol. 55, no. 4, pp. 1390-1404, April 2007.  
  31. M. Elad and M. Aharon, "Image Denoising Via Sparse and Redundant representations over Learned Dictionaries", the IEEE Trans. on Image Processing, Vol. 15, no. 12, pp. 3736-3745, December 2006.
  32. J. Bobin, Y. Moudden, J.-L. Starck, and M. Elad, "Morphological Diversity and Source Separation", the IEEE Signal Processing Letters, Vol. 13, no. 7, pp. 409-412, July 2006.
  33. M. Aharon, M. Elad, and A.M. Bruckstein, "On the Uniqueness of Overcomplete Dictionaries, and a Practical Way to Retrieve Them", the Journal of Linear Algebra and Applications, Vol. 416, pp. 48-67, July 2006.
  34. M. Elad, "Why Simple Shrinkage is Still Relevant for Redundant Representations?",  IEEE Trans. On Information Theory, Vol. 52, no. 12, pp. 5559-5569, December 2006.  
  35. M. Aharon, M. Elad, and A.M. Bruckstein, "The K-SVD: An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation", the IEEE Trans. On Signal Processing, Vol. 54, no. 11, pp. 4311-4322, November 2006.
  36. S. Farsiu, M. Elad, and P. Milanfar, "Video-to-Video Dynamic Super-Resolution for Grayscale and Color Sequences", EURASIP Journal on Applied Signal Processing, Vol. 2006, pp. 1-15,
  37. A. Averbuch, R. Coifman, D.L. Donoho, M. Elad, and M. Israeli, "Fast and Accurate Polar Fourier Transform", the Journal on Applied and Computational Harmonic Analysis, Vol. 21, pp.145-167, 2006.
  38. M. Elad, J-L. Starck, P. Querre, and D.L. Donoho, “Simultaneous Cartoon and Texture Image Inpainting Using Morphological Component Analysis (MCA)”, Journal on Applied and Computational Harmonic Analysis, Vol. 19, pp. 340-358, November 2005.
  39. D.L. Donoho and M. Elad, “On the Stability of the Basis Pursuit in the Presence of Noise”,  EURASIP Signal Processing Journal, Vol. 86, No. 3, pp. 511-532, March 2006.
  40. M. Elad, “Sparse Representations are Most Likely to be the Sparsest Possible”, the Journal on Applied Signal Processing, Vol. 2006, pp. 1-12, 2006. 
  41. S. Farsiu, M. Elad, and P. Milanfar, “Multi-Frame Demosaicing and Super-Resolution of Color Images”,  the IEEE Trans. On Image Processing, Vol. 15, pp. 141-159, January 2006.
  42. D.L. Donoho, M. Elad, and V. Temlyakov, "Stable Recovery of Sparse Overcomplete Representations in the Presence of Noise", the IEEE Trans. On Information Theory, Vol. 52, pp. 6-18, January 2006. 
  43. J.L. Starck, M. Elad, and D.L. Donoho, "Image decomposition via the combination of sparse representations and a variational approach", the IEEE Trans. On Image Processing, Vol. 14, No. 10, pp. 1570-1582, October 2005.
  44. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, "Advanced and Challenges in Super-Resolution", the International Journal of Imaging Systems and Technology, Vol. 14, No. 2, pp. 47-57, Special Issue on high-resolution image reconstruction, August 2004.
  45. J.-L. Starck, M. Elad, and D.L. Donoho, "Redundant Multiscale Transforms and their Application for Morphological Component Analysis", the Journal of Advances in Imaging and Electron Physics, Vol. 132, pp. 287-348, 2004.
  46. J. Tsaig, M. Elad, P. Milanfar, and G. Golub, “A Near-Optimal Filtering Scheme for Low Bit-Rate Block Coders Using Variable Projection”,   IEEE Trans. On Circuits & Systems for Video Technology, Vol. 15, No. 1, pp. 154-160, January 2005.
  47. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Fast and Robust Multi-Frame Super-resolution”, IEEE Trans. On Image Processing, Vol. 13, No. 10, pp. 1327-1344, October 2004.
  48. G. Boutry, M. Elad, G. Golub, and P. Milanfar, “The Generalized Eigenvalue Problem for Non-Square Pencils Using A Minimal Perturbation Approach”,  SIAM Matrix Analysis and Applications (SIMAX), Vol. 27, No. 2, pp. 582-601, November 2005.
  49. M. Elad, R. Kimmel, D. Shaked, and R. Keshet, “Reduced Complexity Retinex Algorithm Via the Variational Approach”, Journal on Visual Communication and Image Representation, Vol.14, No. 4, pp. 369-388, December 2003.
  50. D. L. Donoho and M. Elad, “Optimal Sparse Representation in General (Nonorthogoinal) Dictionaries via L1 Minimization”, the Proc. Nat. Aca. Sci., Vol. 100, pp. 2197-2202, March 2003.
  51. M. Elad, P. Teo, and Y. Hel-Or, “On The Design of Optimal Filters For Gradient-Based Motion Estimation”,  the International Journal on Mathematical Imaging and Vision, Vol. 23, No. 3, pp. 245-365, November 2005.
  52. M. Elad, P. Milanfar, and Gene Golub, “Shape from Moments - An Estimation Theory Perspective”, IEEE Trans. on Signal Processing, Vol. 52, No. 7, pp. 1814-1829, July 2004.
  53. R. Kimmel, D. Shaked, M. Elad, and I. Sobel, “Space Dependent Color Gamut Mapping: A Variational Approach”, IEEE Trans. on Image Processing , Vol. 14, No. 6, pp. 796-803, on June 2005.
  54. R. Kimmel, M. Elad, D. Shaked, R. Keshet, and I. Sobel, “A Variational Framework to Retinex”, the International Journal on Computer Vision, Vol. 52, No. 1, pp. 7-23, April 2003.
  55. M. Elad and A.M. Bruckstein, “A Generalized Uncertainty Principle and Sparse Representation in Pairs of Bases", IEEE Trans. On Information Theory, Vol. 48, pp. 2558-2567, September 2002.
  56. M. Elad, Y. Hel-Or, and R. Keshet, “Pattern Detection Using a Maximal Rejection Classifier”, Pattern Recognition Letters, Vol. 23, No. 12, pp. 1459-1471, October 2002.
  57. M. Elad, “On the Bilateral Filter and Ways to Improve It”, IEEE Transactions On Image Processing, Vol. 11, No. 10, pp. 1141-1151, October 2002.
  58. A. Bruckstein, M. Elad, and R. Kimmel, “Down Scaling for Better Transform Compression”, IEEE Trans. On Image Processing, Vol. 12, No. 9, pp. 1132-1144, September 2003.
  59. M. Elad and Y. Hel-Or, “A Fast Super-Resolution Reconstruction Algorithm for Pure Translational Motion and Common Space Invariant Blur”, IEEE Trans. on Image Processing, Vol.10, No. 8, pp.1187-93, August 2001.
  60. M. Elad and A. Feuer, “Super-Resolution reconstruction of Continuous Image Sequence”, IEEE Trans. On Pattern Analysis and Machine Intelligence (PAMI), Vol. 21, No. 9, pp. 817-834, September 1999.
  61. M. Elad and A. Feuer, “Super-Resolution Restoration of Continuous Image Sequence - Adaptive Filtering Approach”, IEEE Trans. on Image Processing, Vol. 8. No. 3, pp. 387-395, March 1999.
  62. M. Elad and A. Feuer, “Recursive optical Flow Estimation - Adaptive Filtering approach”, Journal of Visual Comm. and Image Representation, Vol. 9, pp. 119-138, June 1998.
  63. M. Elad and A. Feuer, “Restoration of Single Super-Resolution Image From Several Blurred, Noisy and Down-Sampled Measured Images”, IEEE Trans. on Image Processing, Vol. 6, No. 12, pp. 1646-58, December 1997.
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