[2018/06] J. Min, K. H. Jin, M. Unser, and J. C. Ye, "Grid-free localization algorithm using low rank Hankel matrix for super-resolution microscopy," is now accepted in IEEE Trans. on Image Processing [2018/06] H. Gupta, K. H. Jin, H. Q. Nguyen, M. T. McCann, and M. Unser, "CNN-Based projected gradient descent for consistent CT image reconstruction," is now published in IEEE Trans. on Medical Imaging [2018/06] K. Lee, Y. Li, K.H. Jin, and J. C. Ye, "Unified theory for recovery of sparse signals in a general transform domain," is now accepted in IEEE Trans. on Information Theory [2017/11] A Review article for inverse problem with CNN is now appeared. M. T. McCann, K. H. Jin, and M. Unser. "Convolutional Neural Networks for Inverse Problems in Imaging: A Review." IEEE Signal Processing Magazine 34.6 (2017): 85-95.[2017/11] K. H. Jin, and J. C. Ye. "Sparse and Low Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal," IEEE Trans. on Image Processing. vol. 27, no. 3, pp. 1448-1461, March 2018.Code (matlab) is open [github] [2017] K. H. Jin, D. Lee, and J. C. Ye, "A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank Hankel matrix," IEEE Transactions on Computational Imaging, vol. 2, no. 4, pp. 480-495, Dec. 2016.K. H. Jin, M.T. McCann, E. Froustey, M. Unser , "Deep Convolutional Neural Network for Inverse Problems in Imaging." arXiv preprint arXiv:1611.03679 (2016).[2015] ALOHA paper for image inpainting is just published on IEEE Transactions on Image Processing (full title : Annihilating filter based low rank Hankel matrix approach for image inpainting) Application : Image Inpainting on randomly sampled image restoration, object removal, RGB inpainting, etc. [2012] [optics express] High-speed THz reflection tomography - floppy disk & GFRP sample |

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