| Image super-resolution: The techniques, applications, and future L Yue, H Shen, J Li, Q Yuan, H Zhang, L Zhang Signal processing 128, 389-408, 2016 | 510 | 2016 |
| Hyperspectral image denoising employing a spatial–spectral deep residual convolutional neural network Q Yuan, Q Zhang, J Li, H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 57 (2), 1205-1218, 2018 | 397 | 2018 |
| Learning a dilated residual network for SAR image despeckling Q Zhang, Q Yuan, J Li, Z Yang, X Ma Remote Sensing 10 (2), 196, 2018 | 198 | 2018 |
| 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 | 143 | 2019 |
| Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning Q Zhang, Q Yuan, J Li, Z Li, H Shen, L Zhang ISPRS Journal of Photogrammetry and Remote Sensing 162, 148-160, 2020 | 122 | 2020 |
| Cloud removal with fusion of high resolution optical and SAR images using generative adversarial networks J Gao, Q Yuan, J Li, H Zhang, X Su Remote Sensing 12 (1), 191, 2020 | 112 | 2020 |
| Noise removal from hyperspectral image with joint spectral–spatial distributed sparse representation J Li, Q Yuan, H Shen, L Zhang IEEE Transactions on Geoscience and Remote Sensing 54 (9), 5425-5439, 2016 | 95 | 2016 |
| Scene-adaptive remote sensing image super-resolution using a multiscale attention network S Zhang, Q Yuan, J Li, J Sun, X Zhang IEEE Transactions on Geoscience and Remote Sensing 58 (7), 4764-4779, 2020 | 93 | 2020 |
| Hyperspectral image super-resolution by spectral mixture analysis and spatial–spectral group sparsity J Li, Q Yuan, H Shen, X Meng, L Zhang IEEE Geoscience and Remote Sensing Letters 13 (9), 1250-1254, 2016 | 85 | 2016 |
| Spatial–spectral fusion by combining deep learning and variational model H Shen, M Jiang, J Li, Q Yuan, Y Wei, L Zhang IEEE Transactions on Geoscience and Remote Sensing 57 (8), 6169-6181, 2019 | 74 | 2019 |
| SAR image despeckling employing a recursive deep CNN prior H Shen, C Zhou, J Li, Q Yuan IEEE Transactions on Geoscience and Remote Sensing 59 (1), 273-286, 2020 | 58 | 2020 |
| A differential information residual convolutional neural network for pansharpening M Jiang, H Shen, J Li, Q Yuan, L Zhang ISPRS journal of photogrammetry and remote sensing 163, 257-271, 2020 | 54 | 2020 |
| A residual convolutional neural network for polarimetric SAR image super-resolution H Shen, L Lin, J Li, Q Yuan, L Zhao ISPRS journal of photogrammetry and remote sensing 161, 90-108, 2020 | 52 | 2020 |
| DEM generation from contours and a low-resolution DEM X Li, H Shen, R Feng, J Li, L Zhang ISPRS Journal of Photogrammetry and Remote Sensing 134, 135-147, 2017 | 51 | 2017 |
| Deep spatio-spectral Bayesian posterior for hyperspectral image non-iid noise removal Q Zhang, Q Yuan, J Li, F Sun, L Zhang ISPRS journal of photogrammetry and remote sensing 164, 125-137, 2020 | 50 | 2020 |
| Hyperspectral image recovery employing a multidimensional nonlocal total variation model J Li, Q Yuan, H Shen, L Zhang Signal Processing 111, 230-248, 2015 | 48 | 2015 |
| Pansharpening with a guided filter based on three-layer decomposition X Meng, J Li, H Shen, L Zhang, H Zhang Sensors 16 (7), 1068, 2016 | 40 | 2016 |
| 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 | 33 | 2019 |
| Spatio–Temporal Relationship and Evolvement of Socioeconomic Factors and PM2.5 in China During 1998–2016 Y Yang, J Li, G Zhu, Q Yuan International journal of environmental research and public health 16 (7), 1149, 2019 | 23 | 2019 |
| 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 | 21 | 2019 |
