20 citations · 54 across the 15 of their papers we have counts for
6 papers · 1 filter
Image Denoising by Gaussian Patch Mixture Model and Low Rank Patches
Jing Guo, Shuping Wang, Chen Luo +2
Non-local self-similarity based low rank algorithms are the state-of-the-art methods for image denoising. In this paper, a new method is proposed by solving two issues: how to impr…
Dictionary Learning with Low-rank Coding Coefficients for Tensor Completion
Tai-Xiang Jiang, Xi-Le Zhao, Hao Zhang +1
In this paper, we propose a novel tensor learning and coding model for third-order data completion. Our model is to learn a data-adaptive dictionary from the given observations, an…
Tensor train rank minimization with nonlocal self-similarity for tensor completion
Meng Ding, Ting-Zhu Huang, Xi-Le Zhao +2
The tensor train (TT) rank has received increasing attention in tensor completion due to its ability to capture the global correlation of high-order tensors ().…
Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections
Hao Zhang, Xi-Le Zhao, Tai-Xiang Jiang +1
In this paper, we propose a novel low-tubal-rank tensor recovery model, which directly constrains the tubal rank prior for effectively removing the mixed Gaussian and sparse noise…
Deep Plug-and-play Prior for Low-rank Tensor Completion
Xi-Le Zhao, Wen-Hao Xu, Tai-Xiang Jiang +2
Multi-dimensional images, such as color images and multi-spectral images, are highly correlated and contain abundant spatial and spectral information. However, real-world multi-dim…
A Fast Algorithm for Cosine Transform Based Tensor Singular Value Decomposition
Wen-Hao Xu, Xi-Le Zhao, Michael Ng
Recently, there has been a lot of research into tensor singular value decomposition (t-SVD) by using discrete Fourier transform (DFT) matrix. The main aims of this paper are to pro…