187 citations · 1.2k across the 42 of their papers we have counts for
25 papers · 1 filter
Low-Rank Tensor Completion Based on Fractional Regularization with Ky Fan p-k Norm
Shan Fan, Feng Zhang, Jianjun Wang +2
This paper addresses low-rank tensor completion (LRTC) by proposing a novel nonconvex surrogate, namely the ratio of the tensor nuclear norm to the tensor Ky Fan p-k norm (TNPK), t…
DTR: A Unified Deep Tensor Representation Framework for Multimedia Data Recovery
Ting-Wei Zhou, Xi-Le Zhao, Jian-Li Wang +4
Recently, the transform-based tensor representation has attracted increasing attention in multimedia data (e.g., images and videos) recovery problems, which consists of two indispe…
Hyperspectral and multispectral image fusion with arbitrary resolution through self-supervised representations
Ting Wang, Zipei Yan, Jizhou Li +3
The fusion of a low-resolution hyperspectral image (LR-HSI) with a high-resolution multispectral image (HR-MSI) has emerged as an effective technique for achieving HSI super-resolu…
NeurTV: Total Variation on the Neural Domain
Yisi Luo, Xile Zhao, Kai Ye +1
Recently, we have witnessed the success of total variation (TV) for many imaging applications. However, traditional TV is defined on the original pixel domain, which limits its pot…
Revisiting Nonlocal Self-Similarity from Continuous Representation
Yisi Luo, Xile Zhao, Deyu Meng
Nonlocal self-similarity (NSS) is an important prior that has been successfully applied in multi-dimensional data processing tasks, e.g., image and video recovery. However, existin…
H2TF for Hyperspectral Image Denoising: Where Hierarchical Nonlinear Transform Meets Hierarchical Matrix Factorization
Jiayi Li, Jinyu Xie, Yisi Luo +2
Recently, tensor singular value decomposition (t-SVD) has emerged as a promising tool for hyperspectral image (HSI) processing. In the t-SVD, there are two key building blocks: (i)…
Uncertainty-Aware Unsupervised Image Deblurring with Deep Residual Prior
Xiaole Tang, Xile Zhao, Jun Liu +3
Non-blind deblurring methods achieve decent performance under the accurate blur kernel assumption. Since the kernel uncertainty (i.e. kernel error) is inevitable in practice, semi-…
Unsupervised Image Deraining: Optimization Model Driven Deep CNN
Changfeng Yu, Yi Chang, Yi Li +2
The deep convolutional neural network has achieved significant progress for single image rain streak removal. However, most of the data-driven learning methods are full-supervised…
Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity
Yuntong Ye, Changfeng Yu, Yi Chang +4
Image deraining is a typical low-level image restoration task, which aims at decomposing the rainy image into two distinguishable layers: the clean image layer and the rain layer.…
Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion
Ben-Zheng Li, Xi-Le Zhao, Teng-Yu Ji +2
The linear transform-based tensor nuclear norm (TNN) methods have recently obtained promising results for tensor completion. The main idea of this type of methods is exploiting the…
Fully-Connected Tensor Network Decomposition for Robust Tensor Completion Problem
Yun-Yang Liu, Xi-Le Zhao, Guang-Jing Song +2
The robust tensor completion (RTC) problem, which aims to reconstruct a low-rank tensor from partially observed tensor contaminated by a sparse tensor, has received increasing atte…
Nonlocal Patch-Based Fully-Connected Tensor Network Decomposition for Remote Sensing Image Inpainting
Wen-Jie Zheng, Xi-Le Zhao, Yu-Bang Zheng +1
Remote sensing image (RSI) inpainting plays an important role in real applications. Recently, fully-connected tensor network (FCTN) decomposition has been shown the remarkable abil…
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…
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…
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…
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…
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…
Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration
Yi Chang, Luxin Yan, Houzhang Fang +2
Hyperspectral imaging, providing abundant spatial and spectral information simultaneously, has attracted a lot of interest in recent years. Unfortunately, due to the hardware limit…