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Publications

Other Publications


**** BOOK **** M. Elad " Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing" , Springer, 2010. A Matlab-package that reproduces the book's figures and contains most of the discussed algorithms is available here.
  1. Jereias Sulam, Vardan Papyan, Yaniv Romano, and Michael Elad Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning, Arxiv-Math 1708.08705, August 2017.
  2. Vardan Papyan, Yaniv Romano, Jereias Sulam, and Michael Elad Convolutional Dictionary Learning via Local Processing, Arxiv-Math 1705.03239, May 2017.
  3. Dmitry Batenkov, Yaniv Romano, and Michael Elad On the Global-Local Dichotomy in Sparsity Modeling, Arxiv-Math 1702.03446, February 2017.
  4. Yaniv Romano, Michael Elad and Peyman Milanfar The Little Engine that Could: Regularization by Denoising (RED), Arxiv-Math 1611.02862, November 2016.
  5. Amir Adler, Michael Elad, and Michael Zibulevsky Compressed Learning: A Deep Neural Network Approach, Arxiv-Math 1610.09615, October 2016.
  6. Yael Yankelevsky and Michael Elad Structure-Aware Classification using Supervised Dictionary Learning, Arxiv-Math 1609.09199, September 2016.
  7. Yi Ren, Yaniv Romano, and Michael Elad Example-Based Image Synthesis via Randomized Patch-Matching, Arxiv-Math 1609.07370, September 2016.
  8. Michael Elad and Peyman Milanfar Style-Transfer via Texture-Synthesis, Arxiv-Math 1609.03057, September 2016.
  9. Vardan Papyan, Yaniv Romano and Michael Elad Convolutional Neural Networks Analyzed via Convolutional Sparse Coding, Arxiv-Math 1607.08194, July 2016.
  10. Vardan Papyan, Jeremias Sulam, and Michael Elad Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding, Arxiv-Math 1607.02009, July 2016.
  11. Vardan Papyan, Jeremias Sulam, and Michael Elad Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding, Arxiv-Math 1607.02005, July 2016.
  12. Amir Adler, David Boublil, Michael Elad, and Michael Zibulevsky A Deep Learning Approach to Block-based Compressed Sensing of Images, Arxiv-Math 1606.01519, June 2016.
  13. Yaniv Romano and Michael Elad Con-Patch: When a Patch Meets its Context, Arxiv-Math 1603.06812, June 2016.
  14. Gregory Vaksman, Michael Zibulevsky, and Michael Elad Patch-Ordering as a Regularization for Inverse Problems in Image Processing, Arxiv-Math 1602.08510, February 2016.
  15. Jeremias Sulam, Boaz Ophir, Michael Zibulevsky, and Michael Elad Trainlets: Dictionary Learning in High Dimensions, Arxiv-Math 1602.00212, May 2016.
  16. Arie Rond, Raja Giryes, and Michael Elad Poisson Inverse Problems by the Plug-and-Play scheme, Arxiv-Math 1511.02500, November 2015.
  17. Yehuda Dar, Alfred M. Bruckstein, Michael Elad, and Raja Giryes Postprocessing of Compressed Images via Sequential Denoising, Arxiv-Math 1510.09041, March 2016.
  18. Alona Goltz and Michael Elad Linearized Kernel Dictionary Learning, Arxiv-Math 1509.05634, Spetember 2015.
  19. Wen-Ze Shao and Michael Elad Simple, Accurate, and Robust Nonparametric Blind Super-Resolution, Arxiv-Math 1503.03187, March 2015.
  20. Yaniv Romano and Michael Elad Boosting of Image Denoising Algorithms, Arxiv-Math 1502.06220, March 2015.
  21. Wen-Ze Shao, Hai-Bo Li, and Michael Elad Bi-l0-l2-Norm Regularization for Blind Motion Deblurring, Arxiv-Math 1408.4712, August 2014.
  22. Raja Giryes, Michael Elad, and Alfred Bruckstein, Sparsity Based Methods for Overparametrized Variational Problems, Arxiv-Math 1405.4969, May 2014.
  23. Joseph Shtok, Michael Zibulevsky, and Michael Elad, Spatially-Adaptive Reconstruction in Computed Tomography using Neural Networks, Arxiv-Math 1311.7251, November 2013.
  24. Raja Giryes and Michael Elad, Sparsity Based Poisson Denoising with Dictionary Learning, Arxiv-Math 1309.4306, September 2013.
  25. Raja Giryes and Michael Elad, Image Processing using Smooth Ordering of its Patches, Arxiv-Math 1303.5655, March 2013.
  26. Raja Giryes, Sangnam Nam, Michael Elad, Rémi Gribonval, and Mike E. Davies, Greedy-Like Algorithms for the Cosparse Analysis Model, Arxiv-Math 1207.2456, January 2013.
  27. Idan Ram, Michael Elad, and Israel Cohen, Can we allow linear dependencies in the dictionary in the sparse synthesis framework?, Arxiv-Math 1210.3832, October 2012.
  28. Tomer Peleg and Michael Elad, Performance Guarantees of the Thresholding Algorithm for the Co-Sparse Analysis Model, Arxiv-Math 1203.2769, March 2012.
  29. Tomer Peleg, Yonina C. Eldar, and Michael Elad, Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery, Arxiv-Math 1010.5734, March 2012.
  30. Idan Ram, Michael Elad, and Israel Cohen, Redundant Wavelets on Graphs and High Dimensional Data Clouds", Arxiv-Math 1111.4619, November 2011.
  31. Sangnam Nam, Mike E. Davies, Michael Elad, and Rémi Gribonval, The Cosparse Analysis Model and Algorithms, Arxiv-Math 1106.4987, JUne 2011.
  32. Idan Ram, Michael Elad, and Israel Cohen, Generalized Tree-Based Wavelet Transform, Arxiv-Math 1011.4615, February 2011.
  33. Raja Giryes and Michael Elad, RIP-Based Near-Oracle Performance Guarantees for Subspace-Pursuit, CoSaMP, and Iterative Hard-Thresholding, Arxiv-Math 1005.4539, May 2010.
  34. Joseph Shtok, Michael Zibulevsky, and Michael Elad, Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning, Arxiv-Math 1004.4373, April 2010.
  35. Joseph Shtok and Michael Elad, Analysis of Basis Pursuit Via Capacity Sets, Arxiv-Math 1004.4329, April 2010.
  36. Raja Giryes, Michael Elad, and Yonina C. Eldar, The Projected GSURE for Automatic Parameter Tuning in Iterative Shrinkage Methods, Arxiv-Math 1003.3985, March 2010.
  37. Javier Turek, Irad Yavneh, Matan Protter, and Michael Elad, On MMSE and MAP Denoising Under Sparse Representation Modeling Over a Unitary Dictionary, Arxiv-Math 1003.3984, March 2010.
  38. Zvika Ben-Haim, Yonina C. Eldar, and Michael Elad, Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise, Arxiv-Math 0903.4579, March 2009.

  1. M. Elad, Five Lectures on Sparse and Redundant Representations Modelling of Images, Book Chapters in "Mathematics in Image Processing" edited by Hongkai Zhao, AMS Publishing.
  2. M. Protter and M. Elad Super-Resolution With Probabilistic Motion Estimation , Book Chapter in Super-Resolution Imaging, CRC Press, 2010, Peyman Milanfar (Editor).
  3. 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.

  1. M. Elad,Elementary Course in Signal and Image Processing, (in Hebrew), Lecture Notes, Technion 2005.
  2. M. Elad,Mathematical Methods for Engineering, (in Hebrew), Lecture Notes, Technion 2006.
  3. M. Elad,Introduction to Image Processing, (in Hebrew), Lecture Notes, Technion 1999.
  4. M. Elad,Numerical Methods in Optimization, (in Hebrew), Lecture Notes, Technion 1998.