Publications by tag

Tag

Classification    Closed-Form    Compressed Sensing    Convex    Denoising    Doubly Sparse    Image Denoising    Imaging    Mri    Online    Overcomplete    Square    Structured    Theory    Video Denoising    

Classification

  1. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  2. B. Wen, S. Ravishankar, and Y. Bresler, “Learning overcomplete sparsifying transforms with block cosparsity,” in Proc. IEEE International Conference on Image Processing (ICIP), 2014.

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Closed-Form

  1. S. Ravishankar and Y. Bresler, “\ell_0 Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees,” IEEE Trans. Signal Process., vol. 63, no. 9, May 2015.
  2. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  3. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.
  4. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  5. S. Ravishankar and Y. Bresler, “Closed-Form Optimal Updates In Transform Learning,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  6. S. Ravishankar and Y. Bresler, “Sparsifying transform learning for Compressed Sensing MRI,” in Proc. IEEE Int. Symp. Biomed. Imag., 2013.
  7. S. Ravishankar and Y. Bresler, “Closed-form solutions within sparsifying transform learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.

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Compressed Sensing

  1. S. Ravishankar and Y. Bresler, “Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing,” IEEE Transactions on Computational Imaging, vol. 2, no. 3, 2016.
  2. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  3. S. Ravishankar and Y. Bresler, “Data-driven adaptation of a union of sparsifying transforms for blind compressed sensing MRI reconstruction,” in Proc. SPIE, 2015, vol. 9597.
  4. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.

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Convex

  1. S. Ravishankar and Y. Bresler, “Doubly sparse transform learning with convergence guarantees,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.

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Denoising

  1. B. Wen, Y. Li, and Y. Bresler, “When Sparsity Meets Low-Rankness: Transform Learning With Non-Local Low-Rank Constraint for Image Restoration,” in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
  2. 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 Proc. IEEE International Conference on Computer Vision (ICCV), 2017.
  3. B. Wen, S. Ravishankar, and Y. Bresler, “FRIST — Flipping and Rotation Invariant Sparsifying Transform Learning and Applications,” Inverse Problems, vol. 33, no. 074007, 2017.
  4. L. Pfister and Y. Bresler, “Automatic parameter tuning for image denoising with learned sparsifying transforms,” in Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on, 2017.
  5. B. Wen, S. Ravishankar, and Y. Bresler, “Learning Flipping and Rotation Invariant Sparsifying Transforms,” in Proc. IEEE International Conference on Image Processing (ICIP), 2016.
  6. S. Ravishankar and Y. Bresler, “\ell_0 Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees,” IEEE Trans. Signal Process., vol. 63, no. 9, May 2015.
  7. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning - Part I: Algorithms,” IEEE Journal of Selected Topics in Signal Process., 2015.
  8. B. Wen, S. Ravishankar, and Y. Bresler, “Video Denoising by Online 3D Sparsifying Transform Learning,” in IEEE Int. Conf. Image Process., 2015.
  9. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  10. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  11. B. Wen, S. Ravishankar, and Y. Bresler, “Learning overcomplete sparsifying transforms with block cosparsity,” in Proc. IEEE International Conference on Image Processing (ICIP), 2014.
  12. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning for Signal Processing,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014.
  13. S. R. B. Wen and Y. Bresler, “Online Sparsifying Transform Learning and Applications,” Gordon Research Conference on Image Science. 2014.
  14. S. Ravishankar and Y. Bresler, “Closed-Form Optimal Updates In Transform Learning,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  15. S. Ravishankar and Y. Bresler, “Learning Overcomplete Signal Sparsifying Transforms,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  16. S. Ravishankar and Y. Bresler, “Closed-form solutions within sparsifying transform learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  17. S. Ravishankar and Y. Bresler, “Learning overcomplete sparsifying transforms for signal processing,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  18. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Images,” IEEE Trans. Image Process., vol. 22, no. 12, 2013.
  19. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms,” IEEE Trans. Signal Process., vol. 61, no. 5, 2013.
  20. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Image Processing,” in IEEE Int. Conf. Image Process., 2012.
  21. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Signal and Image Processing,” in SIAM Conference on Imaging Science, 2012.
  22. B. Wen, S. Ravishankar, and Y. Bresler, “VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising,” IEEE Trans. Image Process. (submitted).

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Doubly Sparse

  1. S. Ravishankar and Y. Bresler, “Doubly sparse transform learning with convergence guarantees,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
  2. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Images,” IEEE Trans. Image Process., vol. 22, no. 12, 2013.
  3. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Image Representation,” in IEEE Int. Conf. Image Process., 2012.

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Image Denoising

  1. L. Pfister and Y. Bresler, “Automatic parameter tuning for image denoising with learned sparsifying transforms,” in Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on, 2017.
  2. S. Ravishankar and Y. Bresler, “\ell_0 Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees,” IEEE Trans. Signal Process., vol. 63, no. 9, May 2015.
  3. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning - Part I: Algorithms,” IEEE Journal of Selected Topics in Signal Process., 2015.
  4. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  5. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  6. B. Wen, S. Ravishankar, and Y. Bresler, “Learning overcomplete sparsifying transforms with block cosparsity,” in Proc. IEEE International Conference on Image Processing (ICIP), 2014.
  7. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning for Signal Processing,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014.
  8. S. R. B. Wen and Y. Bresler, “Online Sparsifying Transform Learning and Applications,” Gordon Research Conference on Image Science. 2014.
  9. S. Ravishankar and Y. Bresler, “Closed-Form Optimal Updates In Transform Learning,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  10. S. Ravishankar and Y. Bresler, “Learning Overcomplete Signal Sparsifying Transforms,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  11. S. Ravishankar and Y. Bresler, “Closed-form solutions within sparsifying transform learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  12. S. Ravishankar and Y. Bresler, “Learning overcomplete sparsifying transforms for signal processing,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  13. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Images,” IEEE Trans. Image Process., vol. 22, no. 12, 2013.
  14. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Image Processing,” in IEEE Int. Conf. Image Process., 2012.
  15. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Signal and Image Processing,” in SIAM Conference on Imaging Science, 2012.

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Imaging

  1. S. Ravishankar and Y. Bresler, “Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing,” IEEE Transactions on Computational Imaging, vol. 2, no. 3, 2016.
  2. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  3. S. Ravishankar and Y. Bresler, “Data-driven adaptation of a union of sparsifying transforms for blind compressed sensing MRI reconstruction,” in Proc. SPIE, 2015, vol. 9597.
  4. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.

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Mri

  1. B. Wen, S. Ravishankar, and Y. Bresler, “FRIST — Flipping and Rotation Invariant Sparsifying Transform Learning and Applications,” Inverse Problems, vol. 33, no. 074007, 2017.
  2. S. Ravishankar and Y. Bresler, “Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing,” IEEE Transactions on Computational Imaging, vol. 2, no. 3, 2016.
  3. B. Wen, S. Ravishankar, and Y. Bresler, “Learning Flipping and Rotation Invariant Sparsifying Transforms,” in Proc. IEEE International Conference on Image Processing (ICIP), 2016.
  4. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  5. S. Ravishankar and Y. Bresler, “Data-driven adaptation of a union of sparsifying transforms for blind compressed sensing MRI reconstruction,” in Proc. SPIE, 2015, vol. 9597.
  6. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.
  7. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  8. S. Ravishankar and Y. Bresler, “Sparsifying transform learning for Compressed Sensing MRI,” in Proc. IEEE Int. Symp. Biomed. Imag., 2013.

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Online

  1. 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 Proc. IEEE International Conference on Computer Vision (ICCV), 2017.
  2. S. Ravishankar and Y. Bresler, “Online Sparsifying Transform Learning - Part II: Convergence Analysis,” IEEE Journal of Selected Topics in Signal Process., 2015.
  3. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning - Part I: Algorithms,” IEEE Journal of Selected Topics in Signal Process., 2015.
  4. B. Wen, S. Ravishankar, and Y. Bresler, “Video Denoising by Online 3D Sparsifying Transform Learning,” in IEEE Int. Conf. Image Process., 2015.
  5. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning for Signal Processing,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014.
  6. S. R. B. Wen and Y. Bresler, “Online Sparsifying Transform Learning and Applications,” Gordon Research Conference on Image Science. 2014.
  7. B. Wen, S. Ravishankar, and Y. Bresler, “VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising,” IEEE Trans. Image Process. (submitted).

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Overcomplete

  1. S. Ravishankar and Y. Bresler, “Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing,” IEEE Transactions on Computational Imaging, vol. 2, no. 3, 2016.
  2. S. Ravishankar and Y. Bresler, “Data-driven adaptation of a union of sparsifying transforms for blind compressed sensing MRI reconstruction,” in Proc. SPIE, 2015, vol. 9597.
  3. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  4. B. Wen, S. Ravishankar, and Y. Bresler, “Learning overcomplete sparsifying transforms with block cosparsity,” in Proc. IEEE International Conference on Image Processing (ICIP), 2014.
  5. S. Ravishankar and Y. Bresler, “Learning Overcomplete Signal Sparsifying Transforms,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  6. S. Ravishankar and Y. Bresler, “Learning overcomplete sparsifying transforms for signal processing,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.

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Square

  1. B. Wen, Y. Li, and Y. Bresler, “When Sparsity Meets Low-Rankness: Transform Learning With Non-Local Low-Rank Constraint for Image Restoration,” in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
  2. 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 Proc. IEEE International Conference on Computer Vision (ICCV), 2017.
  3. B. Wen, S. Ravishankar, and Y. Bresler, “FRIST — Flipping and Rotation Invariant Sparsifying Transform Learning and Applications,” Inverse Problems, vol. 33, no. 074007, 2017.
  4. L. Pfister and Y. Bresler, “Automatic parameter tuning for image denoising with learned sparsifying transforms,” in Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on, 2017.
  5. B. Wen, S. Ravishankar, and Y. Bresler, “Learning Flipping and Rotation Invariant Sparsifying Transforms,” in Proc. IEEE International Conference on Image Processing (ICIP), 2016.
  6. S. Ravishankar and Y. Bresler, “\ell_0 Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees,” IEEE Trans. Signal Process., vol. 63, no. 9, May 2015.
  7. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  8. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.
  9. S. Ravishankar and Y. Bresler, “Online Sparsifying Transform Learning - Part II: Convergence Analysis,” IEEE Journal of Selected Topics in Signal Process., 2015.
  10. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning - Part I: Algorithms,” IEEE Journal of Selected Topics in Signal Process., 2015.
  11. B. Wen, S. Ravishankar, and Y. Bresler, “Video Denoising by Online 3D Sparsifying Transform Learning,” in IEEE Int. Conf. Image Process., 2015.
  12. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  13. S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning for Signal Processing,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014.
  14. S. R. B. Wen and Y. Bresler, “Online Sparsifying Transform Learning and Applications,” Gordon Research Conference on Image Science. 2014.
  15. S. Ravishankar and Y. Bresler, “Closed-Form Optimal Updates In Transform Learning,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, Lausanne, Switzerland, 2013.
  16. S. Ravishankar and Y. Bresler, “Sparsifying transform learning for Compressed Sensing MRI,” in Proc. IEEE Int. Symp. Biomed. Imag., 2013.
  17. S. Ravishankar and Y. Bresler, “Closed-form solutions within sparsifying transform learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
  18. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms,” IEEE Trans. Signal Process., vol. 61, no. 5, 2013.
  19. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Image Processing,” in IEEE Int. Conf. Image Process., 2012.
  20. S. Ravishankar and Y. Bresler, “Learning Sparsifying Transforms for Signal and Image Processing,” in SIAM Conference on Imaging Science, 2012.

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Structured

  1. B. Wen, S. Ravishankar, and Y. Bresler, “FRIST — Flipping and Rotation Invariant Sparsifying Transform Learning and Applications,” Inverse Problems, vol. 33, no. 074007, 2017.
  2. S. Ravishankar and Y. Bresler, “Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing,” IEEE Transactions on Computational Imaging, vol. 2, no. 3, 2016.
  3. B. Wen, S. Ravishankar, and Y. Bresler, “Learning Flipping and Rotation Invariant Sparsifying Transforms,” in Proc. IEEE International Conference on Image Processing (ICIP), 2016.
  4. S. Ravishankar and Y. Bresler, “Data-driven adaptation of a union of sparsifying transforms for blind compressed sensing MRI reconstruction,” in Proc. SPIE, 2015, vol. 9597.
  5. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  6. B. Wen, S. Ravishankar, and Y. Bresler, “Learning overcomplete sparsifying transforms with block cosparsity,” in Proc. IEEE International Conference on Image Processing (ICIP), 2014.
  7. S. Ravishankar and Y. Bresler, “Doubly sparse transform learning with convergence guarantees,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
  8. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Images,” IEEE Trans. Image Process., vol. 22, no. 12, 2013.
  9. S. Ravishankar and Y. Bresler, “Learning Doubly Sparse Transforms for Image Representation,” in IEEE Int. Conf. Image Process., 2012.

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Theory

  1. S. Ravishankar and Y. Bresler, “\ell_0 Sparsifying Transform Learning with Efficient Optimal Updates and Convergence Guarantees,” IEEE Trans. Signal Process., vol. 63, no. 9, May 2015.
  2. S. Ravishankar and Y. Bresler, “Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,” SIAM Journal on Imaging Sciences, vol. 8, no. 4, 2015.
  3. S. Ravishankar and Y. Bresler, “Blind Compressed Sensing Using Sparsifying Transforms,” in Proc. International Conference on Sampling Theory and Applications (SampTA), 2015.
  4. S. Ravishankar and Y. Bresler, “Online Sparsifying Transform Learning - Part II: Convergence Analysis,” IEEE Journal of Selected Topics in Signal Process., 2015.
  5. S. Ravishankar and Y. Bresler, “Efficient Sparsifying Transform Learning and its Applications,” in Gordon Research Conference on Image Science, Easton, MA, 2014.
  6. B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision, 2014.
  7. S. Ravishankar and Y. Bresler, “Doubly sparse transform learning with convergence guarantees,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.

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Video Denoising

  1. B. Wen, S. Ravishankar, and Y. Bresler, “Video Denoising by Online 3D Sparsifying Transform Learning,” in IEEE Int. Conf. Image Process., 2015.
  2. B. Wen, S. Ravishankar, and Y. Bresler, “VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising,” IEEE Trans. Image Process. (submitted).

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