Publications:

More papers info., please visit: Google Scholar Profile (300+ citations)

• A New Operator Splitting Method for the Euler Elastica Model for Image Smoothing
  Liang-Jian Deng, Roland Glowinski, Xue-Cheng Tai
  SIAM Journal on Imaging Sciences, 12(2):1190-1230, 2019.   [pdf]  [Matlab_Code]
  

• The fusion of panchromatic and multispectral remote sensing images via tensor-based sparse modeling and hyper-Laplacian prior
  Liang-Jian Deng, Minyu Feng, Xue-Cheng Tai
  Information Fusion, 52: 76-89, 2019.   [pdf]  [Matlab_Code]
  

• Fastderain: A novel video rain streak removal method using directional gradient priors
  Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
  IEEE Transactions on Image Processing, 28(4): 2089-2102, 2019.   [pdf]  [Code_link]
  

• Unidirectional Sparse Tensor based model for the Noise Removal of Remote Sensing Image
  Hong-Xia Dou, Ting-Zhu Huang, Liang-Jian Deng, Zi-Yao Zhang
  IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019.
  

• Pan-sharpening via ROG-Based Filtering
  Zi-Yao Zhang, Ting-Zhu Huang, Liang-Jian Deng, Jie Huang, Hong-Xia Dou
  IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019.
  

• Bilateral Filter Based Total Variation Regularization for Sparse Hyperspectral Image Unmixing
  X Li, J Huang, Liang-Jian Deng, TZ Huang
  Information Sciences, 2019.
  

• A Rudin-Osher-Fatemi Model-Based Pansharpening Approach Using RKHS and AHF Representation
  J Liu, Liang-Jian Deng, F Fang, T Zeng
  East Asian Journal on Applied Mathematics, 2019.
  

• A total variation and group sparsity based tensor optimization model for video rain streak removal
  YT Wang, XL Zhao, TX Jiang, Liang-Jian Deng, TH Ma, YT Zhang, TZ Huang
  Signal Processing: Image Communication, 73:96-108, 2019.
  

• A variational pansharpening approach based on reproducible kernel Hilbert space and Heaviside function
  Liang-Jian Deng, Gemine Vivone, Weihong Guo, Mauro Dalla Mura, Jocelyn Chanussot
  IEEE Transactions on Image Processing, 27(9): 4330-4344, 2018.   [pdf??]
  

• Joint-Sparse-Blocks and Low-Rank Representation for Hyperspectral Unmixing
  Jie Huang, Ting-Zhu Huang, Liang-Jian Deng Xi-Le Zhao
  IEEE Transactions on Geoscience and Remote Sensing, 57(4):2419-2438, 2018.   [pdf]  [Matlab_Code]
  

• A directional global sparse model for single image rain removal
  Liang-Jian Deng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang
  Applied Mathematical Modelling, 59: 662-679, 2018.   [pdf]  [Matlab_Code]
  

• Directional l0 Sparse Modeling for Image Stripe Noise Removal
  Hong-Xia Dou, Ting-Zhu Huang, Liang-Jian Deng, Xi-Le Zhao, Jie Huang
  Remote Sensing, 10(3): 361, 2018.   [pdf]  [Matlab_Code]
  

• A Framelet-Based Iterative Pan-Sharpening Approach
  Zi-Yao Zhang, Ting-Zhu Huang, Liang-Jian Deng, Jie Huang, Xi-Le Zhao, Chao-Chao Zheng
  Remote Sensing, 10(4): 622, 2018.   [pdf??]
  

• Evolving networks based on birth and death process regarding the scale stationarity
  Zi-Yao Zhang, Ting-Zhu Huang, Liang-Jian Deng, Jie Huang, Xi-Le Zhao, Chao-Chao Zheng
  Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(8): 083118, 2018.
  

• Hyperspectral image restoration using framelet-regularized low-rank nonnegative matrix factorization
  Yong Chen, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng
  Applied Mathematical Modelling, 63: 128-147, 2018.   [pdf??]
  

• Matrix factorization for low-rank tensor completion using framelet prior
  Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le, Zhao, Teng-Yu Ji, Liang-Jian Deng
  Information Sciences, 2018.   [pdf??]
  

• Multispectral image denoising via nonlocal multitask sparse learning
  Ya-Ru Fan, Ting-Zhu Huang, Xi-Le, Zhao, Liang-Jian Deng
  Remote Sensing, 2018
  

• ingle image super-resolution based on approximated Heaviside functions and iterative refinement
  Xiyu Wang, Ting-Zhu Huang, Liang-Jian Deng
  PLoS One, 2018
  

• A novel tensor-based video rain streaks removal approach via utilizing discriminatively intrinsic priors
  Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.   [pdf]  [Supplementary]  [Code_link]
  

• Image Fusion via Dynamic Gradient Sparsity and Anisotropic Spectral-Spatial Total Variation
  Chao-Chao Zheng, Ting-Zhu Huang, Liang-Jian Deng, Xi-Le, Zhao, Hong-Xia Dou
  IEEE International Conference on Image Processing (ICIP), 2017.   [pdf??]
  

• Stripe Noise Removal of Remote Sensing Image with A Directional L0 Sparse Model
  Hong-Xia Dou, Ting-Zhu Huang, Liang-Jian Deng, Yong Chen
  IEEE International Conference on Image Processing (ICIP), 2017.   [pdf??]
  

• A group sparse joint nonnegative matrix factorization model for multiple data integration
  Hong-Xia Dou, Ting-Zhu Huang, Liang-Jian Deng, Yong Chen
  International Centre for Wavelet Analysis and Its Applications (ICCWAMTIP), 2017
  

• Stripe Noise Removal of Remote Sensing Images by Total Variation Regularization and Group Sparsity Constraint
  Yong Chen, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Jie Huang
  Remote Sensing, 9(6): 559, 2017
  

• Group sparsity based regularization model for remote sensing image stripe noise removal
  Yong Chen, Ting-Zhu Huang, Liang-Jian Deng, Xi-Le Zhao, Min Wang
  Neurocomputing, 2017
  

• A non-convex tensor rank approximation for tensor completion
  Teng-Yu Ji, Ting-Zhu Huang, Xi-Le Zhao, Tian-Hui Ma, Liang-Jian Deng
  Applied Mathematical Modelling, 8:410-422, 2017
  

• Single image super-resolution via an iterative reproducing kernel Hilbert space method
  Liang-Jian Deng, Weihong Guo, Ting-Zhu Huang
  IEEE Transactions on Circuits and Systems for Video Technology, 26(11): 2001-2014, 2016.   [pdf]  [Matlab_Code]
  

• Single image super-resolution by approximate Heaviside functions
  Liang-Jian Deng, Weihong Guo, Ting-Zhu Huang
  Information Sciences, 348:107-123, 2016.   [pdf??]  [Code_link???]
  

• Super-resolution via a fast deconvolution with kernel estimation
  Han Yu, Ting-Zhu Huang, Liang-Jian Deng
  EURASIP Journal on Image and Video Processing, 2017(3): 1-11, 2016
  

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