李杰，男，1989年生，武汉大学测绘学院，副教授，博导。主要从事多源遥感图像智能化融合方面的研究工作，光学/SAR影像质量改善、多源多模态数据融合、深度学习、时空大数据挖掘和融合。在国内外期刊共发表学术论文 61 篇，其中第一/通讯 SCI 论文29 篇，3 篇ESI高被引论文，SCI 他引1364 次。获得2018WHISPERS最佳论文奖，全国高等学校测绘类专业青年教师讲课竞赛特等奖、测绘科技进步一等奖（2017），出版学术专著2部。主持了国家自然科学基金面上项目、国家自然科学基金青年项目、湖北省自然科学基金面上项目、博士后特别资助与面上项目等，参与多项国家级/省部级项目。主讲了本科生课程《遥感原理与应用》、《机器学习》、《定量遥感》、《云计算》。担任国家自然科学基金委员会通讯评议专家、近20个国际SCI期刊审稿人。

欢迎对高光谱/高分辨率/SAR遥感图像处理、图像理解、深度学习、水文遥感、大数据分析等方向感兴趣的研究生加盟！

电子邮件：jli89@sgg.whu.edu.cn

相关代码：https://github.com/SGGJerryLi/WHU-SGG-RS-Pro-Group.git

教育简历

2007/9-2011/6，武汉大学，遥感信息工程学院，摄影测量与遥感专业，获工学学士学位

2011/9-2016/6，武汉大学，测绘遥感信息工程国家重点实验室，摄影测量与遥感专业，获工学博士学位

工作经历

2016/07-2018/03，武汉大学，国际软件学院，讲师/博士后

2018/03-2019/06，武汉大学，测绘学院，讲师

2019/06-今，武汉大学，测绘学院，副教授，博导

部分代表论文

F. Wang, J. Li*, Q. Yuan and L. Zhang “Local–Global Feature-Aware Transformer Based Residual Network for Hyperspectral Image Denoising”，IEEE Transactions on Geoscience and Remote Sensing, 2023.

H. Shen, M. Jiang, J. Li*, C. Zhou, Q. Yuan, and L. Zhang, “Coupling Model- and Data-Driven Methods for Remote Sensing Image Restoration and Fusion: Improving Physical Interpretability”, IEEE Geoscience and Remote Sensing Magazine, 2022.

H. Zhao, J. Li*, Q. Yuan, L.g Lin, L. Yue, H. Xue, “Downscaling of soil moisture products using deep learning: Comparison and analysis on Tibetan Plateau”, Journal of Hydrology, 2022.

J. He, Q. Yuan, J. Li*, Y. Xiao, X. Liu, Y. Zou, “DsTer: A Dense Spectral Transformer for Remote Sensing Spectral Super-resolution”, International Journal of Applied Earth Observation and Geoinformation, 2022.

J. Li, W. Sun, M. Jiang, Q. Yuan, “Self-Supervised Pansharpening Based on a Cycle-Consistent Generative Adversarial Network”, IEEE Geoscience and Remote Sensing Letters, 2022.

Y, Yu, J. Li*, Q. Yuan, Q. Shi, H. Shen and L. Zhang , “Coupling Dual Graph Convolution Network and Residual Network for Local Climate Zone Mapping,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022.

L. Lin, H. Shen, J. Li* , “FDFNet: A Fusion Network for Generating High-Resolution Fully PolSAR Images,” IEEE Geoscience and Remote Sensing Letters, 2022.

J. He, Q. Yuan* , J. Li*，L. Zhang “PoNet: A universal physical optimization-based spectral super-resolution network for arbitrary multispectral images,” Information Fusion, vol. 80, pp.205-225, 2022.

J. Gao, Q. Yuan, J. Li, X. Su, “Unsupervised missing information reconstruction for single remote sensing image with Deep Code Regression”, International Journal of Applied Earth Observation and Geoinformation, vol.105, 2021.

J. Xiao，J. Li*，Q. Yuan，L. Zhang,” A Dual-UNet With Multistage Details Injection for Hyperspectral Image Fusion,”   IEEE Transactions on Geoscience and Remote Sensing, 2021.

L. Lin, J. Li, H. Shen, L. Zhao , Q. Yuan and X. Li, “Low-Resolution Fully Polarimetric SAR and High-Resolution Single-Polarization SAR Image Fusion Network”, IEEE Transactions on Geoscience and Remote Sensing, 2021.

J. Li, H. Shen, H. Li, M. Jiang and Q. Yuan, “Radiometric quality improvement of hyperspectral remote sensing images: a technical tutorial on variational framework”, Journal of Applied Remote Sensing, vol.15, no.3, 2021.

D.Liu, J. Li, Q. Yuan, “A Spectral Grouping and Attention-Driven Residual Dense Network for Hyperspectral Image Super-Resolution”, IEEE Transactions on Geoscience and Remote Sensing, vol.59, no.9, 2021.

J. Gao，J. Li*，M. Jiang, “Hyperspectral and Multispectral Image Fusion by Deep Neural Network in a Self-Supervised Manner”, Remote Sensing, vol.13, no.19, pp.3226, 2021.

J. He, J. Li*, Q Yuan*, H. Shen, and L. Zhang, “Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution”, IEEE Transactions on Neural Networks and Learning Systems, 2021.

J. Xiao，J. Li*，Q. Yuan，M. Jiang, L. Zhang,” Physics-based GAN with Iterative Refinement Unit for Hyperspectral and Multispectral Image Fusion,”  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.

D. Chu, H. Shen, X. Guan, J. Chen, X. Li, J. Li, L. Zhang, “Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion,” Remote Sensing of Environment, vol.264, pp.112632, 2021.

S. Zhao, J. Li*, Q. Yuan, H. Shen and L. Zhang, “Can Terrestrial Restoration Methodologies be Transferred to Planetary Hyperspectral Imagery? A Quantitative Intercomparison and Discussion,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5759-5775, 2020

H. Shen, C. Zhou, J. Li*, and Q. Yuan, “SAR Image Despeckling Employing a Recursive Deep CNN Prior,” IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 1, 2020.

H. Shen, L. Lin, J. Li*, Q. Yuan, and L. Zhao, “A residual convolutional neural network for polarimetric SAR image super-resolution,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 161, pp. 90-108, 2020.

M. Jiang, H. Shen, J. Li*, Q. Yuan, and L. Zhang, “A differential information residual convolutional neural network for pansharpening,”ISPRS Journal of Photogrammetry and Remote Sensing, vol. 163, pp. 257-271, 2020.

J. Gao, Q. Yuan, J. Li*, H. Zhang, X. Su. “Cloud removal with fusion of high resolution optical and SAR images using generative adversarial networks”, Remote Sensing, vo.12, no.1, 2020.

Y Yang, J. Li*, G. Zhu, X. Guan and W. Zhu, “The Impact of Multi-Dimensional Urbanization on PM2.5 Concentrations in 261 Cities of China,” IEEE Access, 2020

J. Li, X. Liu, Q. Yuan, H. Shen, and L. Zhang, “Antinoise Hyperspectral Image Fusion by Mining Tensor Low-Multilinear-Rank and Variational Properties,” IEEE Transactions on Geoscience and Remote Sensing, pp. 1-17, 2019.

Q. Zhang, Q. Yuan, J. Li*, X. Liu, H. Shen, and L. Zhang, “Hybrid Noise Removal in Hyperspectral Imagery With a Spatial–Spectral Gradient Network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 7317-7329, 2019

J. He, J. Li*, Q. Yuan, H. Li, and H. Shen, “Spatial–Spectral Fusion in Different Swath Widths by a Recurrent Expanding Residual Convolutional Neural Network,” Remote Sensing, 11(19): 2203, 2019.

H. Shen, M. Jiang, J. Li*, Q. Yuan, Y. Wei, and L. Zhang, “Spatial-Spectral Fusion by Combining Deep Learning and Variational Model,” IEEE Transactions on Geoscience and Remote Sensing, 57 (8), 6169-6181, 2019.

H. Fan, J. Li*, Q. Yuan*, X. Liu, M. Ng, Hyperspectral image denoising with bilinear low rank matrix factorization, Signal Processing, 163, 132-152, 2019

Y Yang, J. Li*, G. Zhu, Q. Yuan, “Spatio-temporal relationship and evolvement of socioeconomic factors and PM2. 5 in China during 1998-2016,” International Journal of Environmental Research and Public Health, 16 (7), 1149, 2019

Q. Yuan, Q. Zhang, J. Li*, H. Shen, L. Zhang, “Hyperspectral image denoising employing a spatial-spectral deep residual convolutional neural network,” IEEE Transactions on Geoscience and Remote Sensing, 57 (2), 1205-1218, 2018

J. Li, Q. Yuan, H. Shen, X. Meng, and L. Zhang, “Hyperspectral Image Super-Resolution by Spectral Mixture Analysis and Spatial-Spectral Group Sparsity,” IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 9, pp. 1250-1254, 2016.

J. Li, Q. Yuan, H. Shen, and L. Zhang, “Noise Removal From Hyperspectral Image With Joint Spectral-Spatial Distributed Sparse Representation,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 9, pp. 5425-5439, 2016.

J. Li, Q. Yuan, H. Shen, and L. Zhang, “Hyperspectral Image Recovery Employing a Multidimensional Nonlocal Total Variation Model,” Signal Processing, vol. 111, pp. 230-248, 2015

J. Li, H. Shen, Q. Yuan, L. Zhang, W. Gong. “Hyperspectral Image Denoising via Multidimensional Nonlocal Model,” the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Gainesville, Florida, USA, 2013.

J. Li, C. Zeng, Q. Yuan, L. Zhang, H. Shen. “Hyperspectral Images Reconstruction Based Super-Pixel Mapping using Cross-Channel Sparse Model,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, Australia, 2013.

胡云泽，李杰*，何江，袁强强, “基于梯度注入策略与结构驱动评价机制的月表落石检测方法研究”, 遥感信息 , 2023.

奖励荣誉

测绘科技进步一等奖，多成因辐射退化遥感数据的质量改善理论、方法与应用，2017

Whispers 2018最佳论文奖， 2018

出版著作

沈焕锋, 袁强强, 李杰, 岳林蔚, 张良培. 遥感数据质量改善之信息复原. 科学出版社, 2018.

李爽, 李杰. 数字图像处理简明教程. 化学工业出版社, 2018.

主要科研项目

国家重点研发计划子课题，复杂模态缺失情况下地表参量重构，2022.12-2026.11, 主持，100万。

湖北省级技术创新计划重点研发专项，多模态大数据融合驱动的城市大气污染监测与预警技术研究，2023.01-2025.12，主持，100万。

国家自然科学基金面上项目，模型驱动与数据驱动耦合的高时-空-谱融合方法研究，2020.1-2023.12，主持。

国家自然科学基金青年基金项目，不同幅宽遥感影像的空-谱分辨率融合方法研究，2018.1-2020.12，主持。

湖北省自然科学基金面上项目，基于时序协同学习的视频遥感影像超分融合技术研究，2018.1-2019.12，主持

中国博士后基金特别资助项目,时-空-谱协同表达的视频与高光谱遥感影像融合方法， 2018.1-2019.12，主持。

中国博士后基金项目, 顾及信息聚类特征的遥感影像空-谱超分辨率重建方法研究，2016.11-2018.10，主持。

高分辨率对地观测系统重大专项，高光谱图像目标识别，2019.12-2021.6，专题组长

高分辨率对地观测系统重大专项，光谱测绘处理，2018.1-2020.12，专题组长

国家重点研发计划，人-地耦合高精度全球土地利用变化模拟技术，2017.7-2022.6，专题组长