5 papers
Multi-Dimensional Visual Data Recovery: Scale-Aware Tensor Modeling and Accelerated Randomized Computation
Wenjin Qin, Hailin Wang, Jiangjun Peng +2
The recently proposed fully-connected tensor network (FCTN) decomposition has demonstrated significant advantages in correlation characterization and transpositional invariance, an…
HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoising
Qizhou Wang, Li Pang, Xiangyong Cao +2
Hyperspectral image (HSI) denoising is essentially ill-posed since a noisy HSI can be degraded from multiple clean HSIs. However, existing deep learning (DL)-based approaches only…
Beyond Low-rankness: Guaranteed Matrix Recovery via Modified Nuclear Norm
Jiangjun Peng, Yisi Luo, Xiangyong Cao +2
The nuclear norm (NN) has been widely explored in matrix recovery problems, such as Robust PCA and matrix completion, leveraging the inherent global low-rank structure of the data.…
Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration
Shuang Xu, Chang Yu, Jiangjun Peng +2
Remote sensing image restoration aims to reconstruct missing or corrupted areas within images. To date, low-rank based models have garnered significant interest in this field. This…
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image
Shuang Xu, Zixiang Zhao, Haowen Bai +4
Hyperspectral images (HSIs) are frequently noisy and of low resolution due to the constraints of imaging devices. Recently launched satellites can concurrently acquire HSIs and pan…