| Hybrid noise removal in hyperspectral imagery with a spatial–spectral gradient network Q Zhang, Q Yuan, J Li, X Liu, H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 57 (10), 7317-7329, 2019 | 148 | 2019 |
| Stripe noise separation and removal in remote sensing images by consideration of the global sparsity and local variational properties X Liu, X Lu, H Shen, Q Yuan, Y Jiao, L Zhang IEEE Transactions on Geoscience and Remote Sensing 54 (5), 3049-3060, 2016 | 91 | 2016 |
| A universal destriping framework combining 1-D and 2-D variational optimization methods X Liu, H Shen, Q Yuan, X Lu, C Zhou IEEE Transactions on Geoscience and Remote Sensing 56 (2), 808-822, 2017 | 60 | 2017 |
| UTRNet: An unsupervised time-distance-guided convolutional recurrent network for change detection in irregularly collected images B Yang, L Qin, J Liu, X Liu IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2022 | 47 | 2022 |
| Hyperspectral image denoising with bilinear low rank matrix factorization H Fan, J Li, Q Yuan, X Liu, M Ng Signal Processing 163, 132-152, 2019 | 34 | 2019 |
| DsTer: A dense spectral transformer for remote sensing spectral super-resolution J He, Q Yuan, J Li, Y Xiao, X Liu, Y Zou International Journal of Applied Earth Observation and Geoinformation 109 …, 2022 | 29 | 2022 |
| From trained to untrained: A novel change detection framework using randomly initialized models with spatial–channel augmentation for hyperspectral images B Yang, Y Mao, L Liu, X Liu, Y Ma, J Li IEEE Transactions on Geoscience and Remote Sensing 61, 1-14, 2023 | 28 | 2023 |
| Antinoise hyperspectral image fusion by mining tensor low-multilinear-rank and variational properties J Li, X Liu, Q Yuan, H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 57 (10), 7832-7848, 2019 | 22 | 2019 |
| Context enhancing representation for semantic segmentation in remote sensing images L Fang, P Zhou, X Liu, P Ghamisi, S Chen IEEE Transactions on Neural Networks and Learning Systems 35 (3), 4138-4152, 2022 | 15 | 2022 |
| IRCNN: An irregular-time-distanced recurrent convolutional neural network for change detection in satellite time series B Yang, L Qin, J Liu, X Liu IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 9 | 2022 |
| A Fast and Effective Irregular Stripe Removal Method for Moon Mineralogy Mapper (M3) S Zhao, Q Yuan, J Li, Y Hu, X Liu, L Zhang IEEE Transactions on Geoscience and Remote Sensing 60, 1-19, 2021 | 8 | 2021 |
| Oblique stripe removal in remote sensing images via oriented variation X Liu, X Lu, H Shen, Q Yuan, L Zhang arXiv preprint arXiv:1809.02043, 2018 | 8 | 2018 |
| The Influence of Image Degradation on Hyperspectral Image Classification C Li, Z Li, X Liu, S Li Remote Sensing 14 (20), 5199, 2022 | 7 | 2022 |
| A novel removal method for dense stripes in remote sensing images X Liu, H Shen, Q Yuan, L Zhang, Q Cheng ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2016 | 7 | 2016 |
| One-step high-quality NDVI time-series reconstruction by joint modeling of gradual vegetation change and negatively biased atmospheric contamination X Liu, H Shen, Q Yuan, X Lu, S Li IEEE Transactions on Geoscience and Remote Sensing 60, 1-17, 2021 | 5 | 2021 |
| Transformer meets GAN: Cloud-free multispectral image reconstruction via multi-sensor data fusion in satellite images C Li, X Liu, S Li IEEE Transactions on Geoscience and Remote Sensing, 2023 | 4 | 2023 |
| An optimization-driven network with knowledge prior injection for HSI denoising Y Li, J Li, J He, X Liu, Q Yuan IEEE Transactions on Geoscience and Remote Sensing 61, 1-17, 2023 | 2 | 2023 |
| Combining Time-Series Variation Modeling and Fuzzy Spatiotemporal Feature Fusion: A novel Approach for unsupervised Flood Mapping using Dual-polarized Sentinel-1 SAR Images C Li, J Liu, X Liu, X Kang, S Li IEEE Transactions on Geoscience and Remote Sensing, 2023 | 1 | 2023 |
| A CNN-Transformer Embedded Unfolding Network for Hyperspectral Image Super-Resolution Y Tang, J Li, L Yue, X Liu, Y Li, Y Xiao, Q Yuan IEEE Transactions on Geoscience and Remote Sensing, 2024 | | 2024 |
