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K. H. Jin, G. Kim, Y. Leblebici, J. C. Ye, M. Unser, "Direct Reconstruction of Saturated Samples in Band-Limited OFDM Signals," arXiv
Summary : non-iterative interpolation using bandlimitedness

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

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

is now accepted in IEEE Trans. on Information Theory

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.

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 Processingvol. 27, no. 3, pp. 1448-1461, March 2018.
Code (matlab) is open [github]

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).

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.

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