187 citations · 800 across the 15 of their papers we have counts for
15 papers
Implicit Neural Feature Fusion Function for Multispectral and Hyperspectral Image Fusion
ShangQi Deng, RuoCheng Wu, Liang-Jian Deng +2
Multispectral and Hyperspectral Image Fusion (MHIF) is a practical task that aims to fuse a high-resolution multispectral image (HR-MSI) and a low-resolution hyperspectral image (L…
LAConv: Local Adaptive Convolution for Image Fusion
Zi-Rong Jin, Liang-Jian Deng, Tai-Xiang Jiang +1
The convolution operation is a powerful tool for feature extraction and plays a prominent role in the field of computer vision. However, when targeting the pixel-wise tasks like im…
Self-Supervised Nonlinear Transform-Based Tensor Nuclear Norm for Multi-Dimensional Image Recovery
Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang +3
In this paper, we study multi-dimensional image recovery. Recently, transform-based tensor nuclear norm minimization methods are considered to capture low-rank tensor structures to…
Tangent Space Based Alternating Projections for Nonnegative Low Rank Matrix Approximation
Guangjing Song, Michael K. Ng, Tai-Xiang Jiang
In this paper, we develop a new alternating projection method to compute nonnegative low rank matrix approximation for nonnegative matrices. In the nonnegative low rank matrix appr…
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…
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…
Nonnegative Low Rank Tensor Approximation and its Application to Multi-dimensional Images
Tai-Xiang Jiang, Michael K. Ng, Junjun Pan +1
The main aim of this paper is to develop a new algorithm for computing nonnegative low rank tensor approximation for nonnegative tensors that arise in many multi-dimensional imagin…
Hyperspectral Image Super-resolution via Deep Spatio-spectral Convolutional Neural Networks
Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng +3
Hyperspectral images are of crucial importance in order to better understand features of different materials. To reach this goal, they leverage on a high number of spectral bands.…
Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion
Tai-Xiang Jiang, Michael K. Ng, Xi-Le Zhao +1
The main aim of this paper is to develop a framelet representation of the tensor nuclear norm for third-order tensor completion. In the literature, the tensor nuclear norm can be c…
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…
Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery
Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao +3
As low-rank modeling has achieved great success in tensor recovery, many research efforts devote to defining the tensor rank. Among them, the recent popular tensor tubal rank, defi…
Rain Streak Removal for Single Image via Kernel Guided CNN
Ye-Tao Wang, Xi-Le Zhao, Tai-Xiang Jiang +3
Rain streak removal is an important issue and has recently been investigated extensively. Existing methods, especially the newly emerged deep learning methods, could remove the rai…
FastDeRain: A Novel Video Rain Streak Removal Method Using Directional Gradient Priors
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao +2
Rain streak removal is an important issue in outdoor vision systems and has recently been investigated extensively. In this paper, we propose a novel video rain streak removal appr…
Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao +1
In this paper, we investigate tensor recovery problems within the tensor singular value decomposition (t-SVD) framework. We propose the partial sum of the tubal nuclear norm (PSTNN…