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20172026
most citedWeighted Low-rank Tensor Recovery for Hyperspectral Image Restoration

31 citations · 98 across the 22 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.CV2020

Non-Local Robust Quaternion Matrix Completion for Color Images and Videos Inpainting

Zhigang Jia, Qiyu Jin, Michael K. Ng +1

The image nonlocal self-similarity (NSS) prior refers to the fact that a local patch often has many nonlocal similar patches to it across the image and has been widely applied in m…

cs.CV2020

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…

cs.CV2020

Unsupervised Hyperspectral Mixed Noise Removal Via Spatial-Spectral Constrained Deep Image Prior

Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang +2

Recently, convolutional neural network (CNN)-based methods are proposed for hyperspectral images (HSIs) denoising. Among them, unsupervised methods such as the deep image prior (DI…

eess.SP2020

Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling

Meng Ding, Xiao Fu, Ting-Zhu Huang +2

This work revisits coupled tensor decomposition (CTD)-based hyperspectral super-resolution (HSR). HSR aims at fusing a pair of hyperspectral and multispectral images to recover a s…

math.NA2020

Fast second-order implicit difference schemes for time distributed-order and Riesz space fractional diffusion-wave equations

Huan-Yan Jian, Ting-Zhu Huang, Xian-Ming Gu +2

In this paper, fast numerical methods are established for solving a class of time distributed-order and Riesz space fractional diffusion-wave equations. We derive new difference sc…

cs.CV2020

Tensor completion via nonconvex tensor ring rank minimization with guaranteed convergence

Meng Ding, Ting-Zhu Huang, Xi-Le Zhao +1

In recent studies, the tensor ring (TR) rank has shown high effectiveness in tensor completion due to its ability of capturing the intrinsic structure within high-order tensors. A…