The following publications are possibly variants of this publication:
- Fast algorithm with theoretical guarantees for constrained low-tubal-rank tensor recovery in hyperspectral images denoisingXi-Le Zhao, Hao Zhang, Tai-Xiang Jiang, Michael K. Ng, Xiongjun Zhang. ijon, 413:397-409, 2020. [doi]
- Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral ImageYu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Yong Chen 0013, Wei He 0003. tgrs, 58(12):8450-8464, 2020. [doi]
- Mixed Noise Removal in Hyperspectral Image via Low-Fibered-Rank RegularizationYu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang, Tian-Hui Ma, Teng-Yu Ji. tgrs, 58(1):734-749, 2020. [doi]
- Hyperspectral Image Mixed Noise Removal via Nonlinear Transform-Based Block-Term Tensor DecompositionChuan Wang, Xi-Le Zhao, Hao Zhang, Ben-Zheng Li, Meng Ding 0002. lgrs, 20:1-5, 2023. [doi]
- Hyperspectral Mixed Noise Removal via Spatial-Spectral Constrained Unsupervised Deep Image PriorYi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang, Yu-Bang Zheng, Yi Chang 0002. staeors, 14:9435-9449, 2021. [doi]