孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师
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通讯/办公地址 :


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个人简介Personal Profile 学习与工作经历：Education Experience:
2005.09--2009.06Nanjing University of Science and Technology，InformationandComputingScience， Bachelor
2009.09--2014.10 Nanjing University of Science and Technology，Pattern Recognition and Intelligent system，Ms & Ph.D, Supervisor：Zhihui Wei(韦志辉)
Work Experience:
2015. 09 -- 2018.08 Sungkyunkwan University, School of Electronic and ElectricalEngineering, Post-doctor, Supervisor:Byeungwoo Jeon
2014.12 -- 2019.01 Nanjing University of Information Science and Technology，School of Computer and Software，Lecturer
2019.01-- now Nanjing University of Information Science and Technology，School of Computer and Software，Asssociate Professor
社会兼职：Reviewer of 《Knowledge-Based Systems》，《IEEE Transaction on Geoscience and Remote Sensing》,《IEEE Geoscience and Remote Sensing Letters》,《IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 》,《IEEE Transactions on Cybernetics》,《IEEE Transactions on Circuits and Systems for Video Technology》,《IEEE Transactions on Neural Network and Learning System》
研究领域：My research interests cover image processing especially for hyperspectral imagery, including unmixing, restoration, classification, fusion, target detectionetc.
研究领域：计算机视觉、图像处理、模式识别。主要从事遥感信息处理方面的研究，诸如高光谱遥感图像解混、分类、恢复、融合、目标检测等
欢迎感兴趣的研究生加入课题组，要求：对科研感兴趣，具有扎实的数学功底、编程能力出色（Matlab，Python, C或C++）、有较好的主动学习能力、英语六级及以上。
联系邮箱：sunlecncom@163.com
科研成果：项目：
0.国家自然科学基金面上项目，**,基于子空间低秩张量分解的高光谱图像压缩感知快照成像理论与方法， 2020.01-2023.12， 58万元，在研，主持
1.国家自然科学额基金青年项目，**，多/高光谱图像融合分类的结构化低秩学习方法研究，2017/01-2019/12，22万元，在研，主持
2.江苏省自然科学基金青年项目，BK**，多源数据辅助的高光谱图像稀疏字典学习分类方法，2016/07-2018/06，20万元，在研，主持
3.国家自然科学基金面上项目，**，联合空谱上下文的高光谱遥感图像低秩表示分类理论与算法，2015/01-2018/12，80万元，在研，参与
4.国家自然科学基金青年项目，**，空谱联合相关性驱动的高光谱图像概率图修补模型与算法， 2014/01-2016/12，25万元，已结题，参与
5.国家自然科学基金青年项目，**，基于Gini指数的高光谱图像空、谱相关稀疏性分析及压缩感知联合重建方法研究，2014/01-2016/12，24万元，已结题，参与
6.国家自然科学基金青年项目，**，基于空谱联合稀疏性的高光谱解混理论与算法，2012/01-2014/12，25万元，已结题，参与
7.江苏省自然科学基金，BK**，高光谱数据稀疏性特征挖掘和目标分类识别研究，2011/05-2014/05，10万元，已结题，参与
8.中国地质调查局航空高光谱成像系统集成与示范应用项目，27，机载高光谱数据辐射校正并行预处理技术研究及其野外试验数据验证，2011/01-2014/12，120万元，已结题，参与
第一作者通讯作者文章：

[1]Le Sun, Zebin Wu, Jianjun Liu, Liang Xiao, Zhihui Wei. Supervised Spectral-spatial Hyperspectral Image Classification with Weighted Markov Random Fields. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(3): 1490-1503. (SCI, IF:4.942)
[2]Le Sun, Zebin Wu, Liang Xiao, Jianjun Liu, Zhihui Wei. A Novel L1/2 Sparse Regression Method for Hyperspectral Unmixin. International Journal of Remote Sensing, 2013, 34(20): 6983-7001. (SCI, IF:1.724)
[3]Sun Le, Wu Zebin, Liu Jianjun and Wei Zhihui. A Novel Supervised Method for Hyperspectral Image Classification with Spectral-Spatial Constraints. Chinese Journal of Electronics, 2014, 23(CJE-1): 135-141.(SCIE, IF:0.513）
[4]Le Sun, Zebin Wu, Zhihui Wei, Jiangjun Liu, Xingxiu Li. Supervised Hyperspectral Image Classification Combining Sparse Unmixing and Spatial Constraint. International Conference on Computer Vision in Remote Sensing (CVRS), Xiamen, 2012, pp. 110-115. (Best Student Paper Award, ISTP, EI)
[5]Le Sun, Zebin Wu, Jianjun Liu, Zhihui Wei. Supervised Hyperspectral image Classification using Sparse Logistic Regression and Spatial-TV Regularization. International Geoscience and Remote Sensing Symposium, Melbourne, Australia, 2013, pp.1019-1022. (EI）
[6]孙乐，吴泽彬，肖亮，刘建军，韦志辉.一种新的两分类器融合的空谱联合高光谱分类方法. 电子学报，2015，43(11)， pp.2210-2217. (EI)
[7]孙乐，吴泽彬，黄婷婷，刘建军，韦志辉. 大规模高光谱遥感图像处理及其在东天山矿物识别中的应用. Proceedings of 2010 International Conference on Remote Sensing (ICRS 2010) ，Hangzhou, 2010 pp.1-4。
[8]Le Sun, Hiuk Jae Shim, Byeungwoo Jeon^*, Yuhui Zheng, Yunjie Chen, Liang Xiao, Zhihui Wei. Hyperspectral Image Classification Using Multinomial Logistic Regression and Non-local Prior on Hidden Fields. International Conference on Progress in Informatics and Computing, Nanjing, P.R. China, 2015.12.18-12.20 (EI)
[9]Le Sun, Byeungwoo Jeon^*, Yuhui Zheng, Yunjie Chen, Hyperspectral Unmixing based on L1-L2 Sparsity and Total Varization. International Conference on Image Processing (ICIP2016), Pheonix, Arizona, U.S., Sep.25-28, 2016. (EI)
[10] 陈允杰，葛魏东，孙乐^*，一种基于协同稀疏和全变差的高光谱线性解混方法，自动化学报，2016. (EI)
[11]Le Sun，Yuhui Zheng，and Byeungwoo Jeon. Hyperspectral Restoration Employing Low Rank and 3D Total Variation Regularization. IEEE International Conference on Progress in Informatics and Computing, Dec. 22-25, Shanghai, China, 2016. (EI)
[12]Le Sun, Byeungwoo Jeon, Yuhui Zheng, and Zebin Wu. Homogeneous Region based Low Rank Representation in Hidden Field for Hyperspectral Classification. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul. 23-28, Fort Worth, Texas, USA, 2017. (EI)
[13]Le Sun, Byeungwoo Jeon, Yuhui Zheng, Zebin Wu. Hyperspectral Image Restoration by Using Low Rank Representation on Sspectral Difference Image. IEEE Geoscience and Remote Sensing Letters, 2017, 14(7):1115-1155. (SCI, IF:2.761)
[14]Le Sun, Byeungwoo Jeon. A Novel Subspace Spatial-spectral Low Rank Learning Method for Hyperspectral Denoising. IEEE Visual Communication and Image Processing, Dec. 10-13, St. Petersburg, Florida, USA, 2017. (EI)
[15]Le Sun, Shunfeng Wang, Jin Wang, Yuhui Zheng, Byeungwoo Jeon. Hyperspectral classification employing spatial–spectral low rank representation in hidden fields. Journal of Ambient Intelligence and humanized Computing, pp. 1-12,2017. Doi: 10.1007/s12652-017-0586-1 (SCIE, IF:1.588)
[16]Le Sun, Byeungwoo Jeon, Yuhui Zheng, Zebin Wu. A novel weighted cross total variation method for hyperspectral image mixed denoising. IEEE Access, pp. 1-17, 2017. Doi: 10.1109/ACCESS.2017.** (SCI, IF:3.244)
[17]Le Sun， Byeungwoo Jeon, Yuhui Zheng, Hyperspectral Restoration based on Total Variation Regularized Low Rank Decomposition in Spectral Difference Space，International Workshop on Advanced Image Technology 2018 (IWAIT 2018), IEEE, Chiangmai, Thailand, 2018.01. 07-01.09
[18]Le Sun，Byeungwoo Jeon(*), Bushra Naz Soomro, Yuhui Zheng, Zebin Wu，Liang Xiao，Fast Superpixel based Subspace Low Rank Learning Method for Hyperspectral Denoising，IEEE Access，2018, doi: 10.1109/ACCESS.2018.**
[19]Le Sun, Tianming Zhan, Zebin Wu, Byeungwoo Jeon.A Novel 3D Anisotropic Total Variation Regularized Low Rank Method for Hyperspectral Image Mixed Denoising. ISPRS International Journal of Geoinformation, 2018, 7(10):412.
[20]Le Sun, Tianming Zhan, Zebin Wu, Liang Xiao, Byeungwoo Jeon. Hyperspectral Mixed Denoising via Spectral Difference-induced Total Variation and Low-rank Approximation. Remote Sensing, 2018.
[21]Le Sun, Weidong Ge, Yunjie Chen, Jianwei Zhang, Byeungwoo Jeon. Hyperspectral unmixing empoying L1-L2 sparsity and total variation. International Journal of Remote Sensing, 2018, 39(19):6037-6060
[22]Le Sun, Chenyang Ma, Yunjie Chen, Hiuk Jae Shim, Zebin Wu and Byeungwoo Jeon.Adjacent Superpixel-Based Multiscale Spatial-Spectral Kernel for Hyperspectral Classification, IEEE JSTARS, 2019, 12(6):1905-1919.
[23]Qian Liu ; Zebin Wu ;Le Sun; Yang Xu ; Lu Du ; Zhihui Wei.Kernel Low-Rank Representation Based on Local Similarity for Hyperspectral Image Classification,IEEE Journal of Selected Topics in Applied Earth Obsevations and Remote Sensing, vol. 12, no. 6, pp. 1920-1932, 2019.
[24]Sun Le; Ma Chenyang; Chen Yunjie; Zheng Yuhui*;Shim Hiuk Jae; Wu Zebin; Jeon Byeungwoo; Low rank component induced spatial-spectral kernel method for hyperspectral image classification,IEEE Transactions on Circuits and Systems for Video Technology, 30(10): 3829 - 3842, 2020. DOI:10.1109/TCSVT.2019.**.
[25]Sun Le; Wu Feiyang; Tianming Zhan*; Liu Wei; Wang Jin; Jeon Byeungwoo; Weighted nonlocal low-rank tensor decomposition method for sparse unmixing of hyperspectral images,IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp 1174-1188, 2020.
[26] Jinwei Wang, Xiaongbo Song,Le Sun*, et al., A novel cubic convolutional Neural Network for hyperspectral image classification,IEEE Journal of Selected Topics in Applied Earth Obsevations and Remote Sensing, vol. 13, pp. 4133-4148, 2020, DOI:10.1109/JSTARS.2020.**
[27] Zhenyu Lu, Bin Xu,Le Sun*, et al, 3-D Channel and Spatial Attention Based Multiscale Spatial–Spectral Residual Network for Hyperspectral Image Classification,IEEE Journal of Selected Topics in Applied Earth Obsevations and Remote Sensing, vol. 13, pp. 4311-4324, 2020. Doi: 10.1109/JSTARS.2020.**
[28]Le Sun, Feiyang Wu, Chengxun He, et al., Weighted Collaborative Sparse and L1/2 Low-Rank Regularizations with Superpixel Segmentation for Hyperspectral Unmixing,IEEE Geoscience and Remote Sensing Letters, 2020. Doi:10.1109/LGRS.2020.**.
[29]Le Sun, Chengxun He, Yuhui Zheng, Songze Tang.SLRL4D: Joint Restoration of Subspace Low-Rank Learning and Non-local 4-D Transform Filtering for Hyperspectral Image, Remote Sensing, 12(18), 2979, 2020.
[30]Chengxun He, Le Sun*, Wei Huang, Jianwei Zhang, Yuhui Zheng, Byeungwoo Jeon. TSLRLN: Tensor Subspace Low-Rank Learning with Non-local Prior for Hyperspectral Image Mixed Denoising. Signal Processing, 2021. Online, doi: 10.1016/j.sigpro.2021.108060.
荣誉：[1] 江苏省科学技术奖二等奖，基于空谱联合结构化特征的高光谱图像分析方法与应用技术，排名 6，2019.
其他学术成就：[1] 孙乐，吴泽彬，韦志辉. 软件著作权，机载高光谱数据大气辐射校正预处理软件，简称【AHARC】，登记号：2014SR013125.
[2] 刘建军，吴泽彬，孙乐，韦志辉. 软件著作权，机载高光谱数据边缘辐射校正预处理软件，简称【AHERC】，登记号：2012SR066151.
[3] 吴泽彬，韦志辉，刘建军，孙乐. 软件著作权，矿产资源高光谱遥感探测数据处理软件，登记号：2011R11S**.
[4] 宋义刚，吴泽彬，韦志辉，孙乐，刘建军. 国家发明专利，基于增强约束稀疏回归的半监督高光谱亚像元目标检测法，登记号：8.8.

教育经历Education Background
工作经历Work Experience
2009.92014.10
南京理工大学
控制科学与工程
博士
2005.92009.6
南京理工大学
信息与计算科学
理学学士
2019.22020.6
南京信息工程大学
讲师（高校）
2015.92018.8
韩国成均馆大学
讲师（高校）
2014.122019.1
南京信息工程大学
讲师（高校）

研究方向Research Focus
社会兼职Social Affiliations
计算机视觉，图像处理（遥感图像分析：解混、分类、融合），多维信号处理
暂无内容

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孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






当前位置： 中文主页 >> 科学研究
研究领域
My research interests cover image processing especially for hyperspectral imagery, including unmixing, restoration, classification, fusion, target detectionetc.
研究领域：计算机视觉、图像处理、模式识别。主要从事遥感信息处理方面的研究，诸如高光谱遥感图像解混、分类、恢复、融合、目标检测等
欢迎感兴趣的研究生加入课题组，要求：对科研感兴趣，具有扎实的数学功底、编程能力出色（Matlab，Python, C或C++）、英文读写能力较好。
联系邮箱：sunlecncom@163.com




论文成果 More>>
孙乐 , Weighted Nonlocal Low-Rank Tensor Decomposition Method for Sparse Unmixing of Hyperspectral Images IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 13, 1174-1188.
孙乐 , Supervised Spectral-spatial Hyperspectral Image Classification with Weighted Markov Random Fields IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 53, 1490-1503.
孙乐 , Hyperspectral Mixed Denoising via Spectral Difference-Induced Total Variation and Low-Rank Approximation REMOTE SENSING 10, 23p.
孙乐 , Hyperspectral Denoising via Cross Total Variation-Regularized Unidirectional Nonlocal Low-Rank Tensor Approximation Internationla Conference on Image Processing
孙乐 , A Novel 3D Anisotropic Total Variation Regularized Low Rank Method for Hyperspectral Image Mixed Denoising ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 7, 23p.
孙乐 , Fast Superpixel based Subspace Low Rank Learning Method for Hyperspectral Denoising IEEE Access 6, 12031 - 12043.

专利
暂无内容

著作成果
暂无内容

科研项目
多/高光谱图像融合分类的结构化低秩学习方法研究, 国家自然科学基金项目, 2016/12/13-2019/12/31, 进行
多源数据辅助的高光谱图像稀疏字典学习分类方法, 省、市、自治区科技项目, 2015/09/10-2018/06/30, 进行
Subspace Low Rank Learning Method for Hyperspectral/Multispectral Image fusion and Classification, 国际合作项目, 2016/07/22-2018/10/31, 完成

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孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






研究领域 当前位置： 中文主页 >> 科学研究 >> 研究领域
My research interests cover image processing especially for hyperspectral imagery, including unmixing, restoration, classification, fusion, target detectionetc.
研究领域：计算机视觉、图像处理、模式识别。主要从事遥感信息处理方面的研究，诸如高光谱遥感图像解混、分类、恢复、融合、目标检测等
欢迎感兴趣的研究生加入课题组，要求：对科研感兴趣，具有扎实的数学功底、编程能力出色（Matlab，Python, C或C++）、英文读写能力较好。
联系邮箱：sunlecncom@163.com

---

孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






论文成果 当前位置： 中文主页 >> 科学研究 >> 论文成果
Weighted Nonlocal Low-Rank Tensor Decomposition Method for Sparse Unmixing of Hyperspectral Images.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING13(-):1174-1188
Supervised Spectral-spatial Hyperspectral Image Classification with Weighted Markov Random Fields.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING53(3):1490-1503
Hyperspectral Mixed Denoising via Spectral Difference-Induced Total Variation and Low-Rank Approximation.REMOTE SENSING10(12):23p
Hyperspectral Denoising via Cross Total Variation-Regularized Unidirectional Nonlocal Low-Rank Tensor Approximation.Internationla Conference on Image Processing
A Novel 3D Anisotropic Total Variation Regularized Low Rank Method for Hyperspectral Image Mixed Denoising.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION7(10):23p
Fast Superpixel based Subspace Low Rank Learning Method for Hyperspectral Denoising.IEEE Access6(-):12031 - 12043
Hyperspectral unmixing employing l1−l2 sparsity and total variation regularization.INTERNATIONAL JOURNAL OF REMOTE SENSING39(19):6037-6060
Adjacent Superpixel-Based Multiscale Spatial-Spectral Kernel for Hyperspectral Classification.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING12(6):1905-1919
Hyperspectral Image Restoration Using Low-Rank Representation on Spectral Difference Image.IEEE Geoscience and Remote Sensing Letters14(7):1151-1155
A Novel Weighted Cross Total Variation Method for Hyperspectral Image Mixed Denoising.IEEE ACCESS5(-):27172-27188
共10条1/1 首页上页下页尾页

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孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






专利 当前位置： 中文主页 >> 科学研究 >> 专利
共0条0/0

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孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






著作成果 当前位置： 中文主页 >> 科学研究 >> 著作成果
共0条0/0

---

孙乐


个人信息Personal Information 副研究员（高校） 硕士生导师
教师拼音名称：sunle
电子邮箱：002631@nuist.edu.cn
所在单位：计算机与软件学院
办公地点：Room 401
性别：男
职称：副研究员（高校）
硕士生导师






科研项目 当前位置： 中文主页 >> 科学研究 >> 科研项目
多/高光谱图像融合分类的结构化低秩学习方法研究
多源数据辅助的高光谱图像稀疏字典学习分类方法
Subspace Low Rank Learning Method for Hyperspectral/Multispectral Image fusion and Classification
共3条1/1 首页上页下页尾页