张洪艳（武大教授）

张洪艳（武大教授）的个人简介

张洪艳教授，男，1983年生，博士毕业于武汉大学测绘遥感信息工程国家重点实验室，目前担任武汉大学测绘遥感信息工程国家重点实验室教授、博士生导师，主要从事高光谱遥感信息处理、农业遥感和机器学习等方向的研究工作。

张洪艳曾荣获武汉大学“珞珈青年学者”，国家留学基金委首批“未来科学家”等荣誉称号，武汉大学“351计划”等人才计划。在国内外学术期刊和会议上发表论文85余篇，其中SCI期刊论文47篇，EI检索论文19篇，学术专著1部，申请国家发明专利3项，论文共被引用2000多次，ESI热点论文2篇， ESI高被引论文4篇，Elsevier年度热门论文1篇。先后主持自然科学基金项目4项、湖北省自然科学基金等省部级科研项目2项。

张教授先后荣获2017年国家测绘科技进步奖一等奖(排名第二)，2016年“创青春”全国大学生创业大赛金奖指导老师，IEEE地球科学与遥感学会2014年度数据融合大赛第三名(全球共40余个参赛团体)，2014年IEEE国际地球科学与遥感大会学生论文竞赛第三名指导老师（全球共80余名参赛者）。

个人简介

教育经历2005/09-2010/06，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，博士2001/09-2005/06，武汉大学，资源与环境科学学院，地理信息系统专业，学士工作经历2016/12-至今，武汉大学测绘遥感信息工程国家重点实验室，破格教授2016/09-2016/11，葡萄牙里斯本大学，访问学者2015/12-2016/08，比利时根特大学，访问学者2013/12-2016/11，武汉大学测绘遥感信息工程国家重点实验室，副研究员2010/08-2013/11，武汉大学测绘遥感信息工程国家重点实验室，讲师学术兼职Computers & Geosciences期刊副主编Geosciences期刊编委IEEE资深会员(IEEE Senior Member)2015 IEEEWHISPERS、2016 IGARSS Session Chair38个国际学术期刊和多个国内核心期刊审稿员

荣誉奖励

2016年，“创青春”全国大学生创业大赛金奖指导老师2015年，国家留学基金委首届“未来科学家”2014年，IEEE地球科学与遥感学会数据融合大赛影像分类赛第三名2014年，IEEE国际地球科学与遥感大会学生论文竞赛第三名指导老师2013年，武汉大学第四批“珞珈青年学者”

学术研究

期刊论文（按时间排列）：

[1] W. He, H. Zhang*, H. Shen, L. Zhang*, "Hyperspectral Image Denoising Using Local Low-Rank Matrix Recovery and Global Spatial-Spectral Total Variation",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 3, pp. 713 - 729, 2018.

[2] Y. Zhang, P. Jiang, H. Zhang, P. Cheng, "Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine",International Journal of Environmental Research and Public Health, vol. 15, no. 2, DOI: 10.3390/ijerph15020186, 2018.

[3] H. Shao, H. Zhang, A. Pi?urica, "A Robust Sparse Representation Model for Hyperspectral Image Classification",Sensors, vol. 17, no. 9, DOI: 10.3390/s17092087, 2017.

[4] H. Fan, Y. Chen, Y. Guo, H. Zhang, G. Kuang, "Hyperspectral Image Restoration Using Low-Rank Tensor Recovery",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2017.2714338, 2017.

[5] W. He,H. Zhang*, L. Zhang, H. Shen, "Total Variation Regularized Reweighted Sparse Non-Negative Matrix Factorization for Hyperspectral Unmixing",IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2017.2683719, 2017.

[6] H. Zhai,H. Zhang*, X. Xu*, L. Zhang, P. Li, "Kernel Sparse Subspace Clustering With a Spatial Max Pooling Operation for Hyperspectral Remote Sensing Data Interpretation",Remote Sensing, vol. 9, no. 4, DOI:10.3390/rs9040335, 2017.

[7] R. Luo, W. Liao,H. Zhang, L. Zhang, Y. Pi, P. Scheunders and W. Philips, "Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS. 2017.2684085, 2017

[8] C. Han, N. Sang,H. Zhang, L. Zhang, "Gradient Transferred Pansharpening Method Based on Cosparse Analysis Model",Journal of Applied Remote Sensing, DOI: 10.1117/1.JRS.11.025009, 2017.

[9] H. Zhai,H. Zhang*, L. Zhang, P. Li, A. Plaza, "A New Sparse Subspace Clustering Algorithm for Hyperspectral Remote Sensing Imagery",IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 1, pp. 43 - 47, 2017.

[10] H. Zhai,H. Zhang*, L. Zhang, P. Li, "Reweighted Mass Center based Object-Oriented Sparse Subspace Clustering for Hyperspectral Images",Journal of Applied Remote Sensing, vol. 10, no. 4, Article ID: 046014, 2016.

[11] L. Yue, H. Shen, J. Li, Q. Yuan,H. Zhang, L. Zhang, "Image super-resolution: the techniques, applications, and future",Signal Processing, vol. 128, pp. 389u2013408, 2016.

[12] X. Meng, J. Li, H. Shen, L. Zhang,H. Zhang, "Pansharpening with a Guided Filter Based on Three-Layer Decomposition",Sensors, vol. 16, no. 7, DOI:10.3390/s16071068, 2016.

[13]H. Zhang, H. Zhai, L. Zhang, P. Li, "Spectral-Spatial Sparse Subspace Clustering for Hyperspectral Remote Sensing Images",IEEE Trans. on Geoscience and Remote Sensing, vol. 54, no. 6, pp. 3672u20133684, June 2016.

[14] W. He,H. Zhang*, L. Zhang, "Sparsity-Regularized Robust Non-Negative Matrix Factorization for Hyperspectral Unmixing",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 9, pp. 4267 - 4279, 2016.

[15] C. Han,H. Zhang*, C. Gao, C. Jiang, N. Sang, L. Zhang, "A Remote Sensing Image Fusion Method Based on the Analysis Sparse Model",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 1, pp. 439 - 453, 2016.

[16] W. He,H. Zhang*, L. Zhang, W. Philips, W. Liao, "Weighted Sparse Graph Based Dimensionality Reduction for Hyperspectral Images",IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 5, pp. 686 - 690, 2016.

[17] C. Jiang,H. Zhang*, L. Zhang, H. Shen, Q. Yuan, "Hyperspectral Image Denoising with a Combined Spatial and Spectral Hyperspectral Total Variation Model",Canadian Journal of Remote Sensing, vol. 42, no. 1, pp. 53 - 72, 2016.

[18] W. He,H. Zhang*, L. Zhang, H. Shen, "Total-Variation-Regularized Low-rank Matrix Factorization for Hyperspectral Image Restoration",IEEE Trans. on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 178 - 188, 2016.(ESI Highly Cited Paper)

[19] J. Li,H. Zhang*, M. Guo, L. Zhang, H.Shen and Q. Du, "Urban Classification by the Fusion ofThermal Infrared Hyperspectraland Visible Data",Photogrammetric Engineering & Remote Sensing,vol. 81, no. 12, pp. 901u2013911. 2015.

[20] J. Li,H. Zhang*, L. Zhang, "Efficient Superpixel-level Multi-task Joint Sparse Representation for Hyperspectral Image Classification",IEEE Trans. on Geoscience and Remote Sensing, vol. 53, no. 10, pp. 5338-5351, 2015.

[21] W. He,H. Zhang*, L. Zhang, H. Shen, "Hyperspectral Image Denoising via Noise-Adjusted Iterative Low-Rank Matrix Approximation",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 3050 - 3061, 2015.

[22] J. Li,H. Zhang*, L. Zhang, "A Nonlinear Multiple Features Learning Classifier for Hyperspectral Image with Limited Training Samples",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2728 - 2738, 2015.

[23] J. Li,H. Zhang*, L. Zhang, L. Ma, "Hyperspectral Anomaly Detection by the Use of Background Joint Sparse Representation",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2523 - 2533, 2015.

[24] X. Ma, H. Shen, L. Zhang, J. Yang,H. Zhang, "Adaptive Anisotropic Diffusion Method for Polarimetric SAR Speckle Filtering",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 3, pp. 1939-1404, 2015.

[25]H. Zhang, L. Zhang, H. Shen, "A Blind Super-resolution Reconstruction Method Considering Image Registration Errors",International Journal of Fuzzy Systems, vol. 17, no. 2, pp. 353-364, 2015.

[26] X. Li, H. Shen, L. Zhang,H. Zhang, Q. Yuan, and G. Yang, "Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multi-temporal Dictionary Learning,"IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 11, pp. 7086 - 7098, 2014.

[27] J. Li,H. Zhang, L. Zhang, X. Huang, L. Zhang, "Joint Collaborative Representation with Multitask Learning for Hyperspectral Image Classification",IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 9, pp. 5923-5936, 2014.

[28]H. Zhang, W. He, L. Zhang, H. Shen, Q. Yuan, "Hyperspectral Image Restoration Using Low-Rank Matrix Recovery",IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 4729-4743, 2014.(ESI Hot Paper, ESI Highly Cited Paper)

[29] J. Li,H. Zhang, L. Zhang, "Column-Generation Kernel Nonlocal Joint Collaborative Representation for Hyperspectral Image Classification",ISPRS Journal of Photogrammetry and Remote Sensing, vol. 94, no. 8, pp. 25-36, 2014.

[30] J. Li,H. Zhang, L. Zhang, "Supervised Segmentation of Very High Resolution Images by the Use of Extended Morphological Attribute Profiles and a Sparse Transform",IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 8, pp. 1409-1413, 2014.

[31] J. Li,H. Zhang, Y. Huang, L. Zhang, "Hyperspectral Image Classification by Nonlocal Joint Collaborative Representation with a Locally Adaptive Dictionary",IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 6, pp. 3707-3719, 2014.(ESI Highly Cited Paper)

[32] T. Hu,H. Zhang*, H. Shen, L. Zhang, "Robust Registration by Rank Minimization for Multiangle Hyper/Multispectral Remotely Sensed Imagery",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2443 - 2457, 2014.

[33]H. Zhang, J. Li , Y. Huang, L. Zhang, "A Nonlocal Weighted Joint Sparse Representation Classification Method for Hyperspectral Imagery",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2056 - 2065, 2014.(ESI Highly Cited Paper)

[34] X. Meng, H. Shen,H. Zhang, L. Zhang, H. Li, "Maximum a Posteriori Fusion Method Based on Gradient Consistency Constraint for Multispectral/Panchromatic Remote Sensing Images,"Spectroscopy and Spectral Analysis, vol. 34, no. 6, pp. 1332-1337, 2014.

[35] C. Jiang,H. Zhang*, H. Shen, L. Zhang, "Two-Step Sparse Coding for the Pan-Sharpening of Remote Sensing Images",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 5, pp. 1792 - 1805, 2014.

[36] M. Guo,H. Zhang*, J. Li, L. Zhang, H. Shen, "An Online Coupled Dictionary Learning Approach for Remote Sensing Image Fusion",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 4, pp. 1284-1294, 2014.

[37] X. Li, H. Shen, L. Zhang,H. Zhang, Q. Yuan, "Dead Pixel Completion of Aqua MODIS Band 6 using a Robust M-Estimator Multi-Regression",IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 4, pp. 768-772, 2014.

[38]H. Zhang, Z. Yang, L. Zhang, H. Shen, "Super-Resolution Reconstruction for Multi-Angle Remote Sensing Images Considering Resolution Differences",Remote Sensing, vol. 6, no. 1, pp. 637-657, 2014.

[39] H. Shen, W. Jiang,H. Zhang, L. Zhang, "A piece-wise approach to removing the nonlinear and irregular stripes in MODIS data",International Journal of Remote Sensing,vol. 35, no. 1, pp. 44-53, 2014.

[40] X. Xu, Y. Zhong, L. Zhang,H. Zhang, "Sub-Pixel Mapping Based on a MAP Model with Multiple Shifted Hyperspectral Imagery",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 580-593, 2013.

[41]H. Zhang, H. Shen, L. Zhang, "A Super-Resolution Reconstruction Algorithm for Hyperspectral Images",Signal Processing, vol. 92, no. 9, pp. 2082-2096, 2012.(2012 Top 25 Hottest Article)

[42] L. Zhang, H. Shen , W. Gong,H. Zhang, "Adjustable Model-Based Fusion Method for Multispectral and Panchromatic Images",IEEE Trans. on Systems, Man and Cybernetics, Part B, vol. 42, no. 6, pp. 1693-1704, 2012.

[43] C. Jiang,H. Zhang, H. Shen, L. Zhang, "A Practical Compressed Sensing based Pan-Sharpening Method",IEEE Geoscience and Remote Sensing Letters, vol. 9, no.4, pp. 629-633, 2012.

[44] L. Zhang,H. Zhang, H. Shen, P. Li, "A Super-Resolution Reconstruction Algorithm for Surveillance Images",Signal Processing, vol. 90, no. 3, pp. 848-859, 2010.

[45] H. Fan, Y. Chen, Y. Guo,H. Zhang, G. Kuang, "Hyperspectral Image Restoration Using Low-Rank Tensor Recovery",IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2017.2714338, 2017.

会议论文（按时间排列）:

[1] S. Huang,H. Zhang, A. Pi?urica, "Robust Joint Sparsity Model for Hyperspectral Image Classification",International Conference on Image Processing (ICIP 2017), Beijing, China, 17u201320 September, 2017.

[2] H. Zhai,H. Zhang, L. Zhang, P. Li, "Total Variation Based Collaborative Representation Model With an Adaptive Sub-Dictionary for Hyperspectral Remote Sensing Imagery Clustering",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2017),Fort Worth, USA, 23u201327 July, 2017.

[3] R. Luo, W. Liao,H. Zhang, Y. Pi, W. Philips, "Spectral-Spatial Classification of Hyperspectral Images with Semi-Supervised Graph Learning",SPIE REMOTE SENSING 2016, Edinburgh, UK, 26-29 September, 2016.

[4] W. Liao, F. Van Coillie,H. Zhang, S. Gautama and W. Philips, "Fusion of Optical and LIDAR Images for Urban Objects Recognition",GEOBIA 2016, Enschede, Netherlands, 14-16 September, 2016.

[5] W. Liao,H. Zhang, J. Li, S. Huang, R. Wang, R. Luo, A. Pi?urica, "Fusion of Spectral and Spatial Information for Land Cover Classification",IEICE Information and Communication Technology Forum 2016, Patras, Greece, 6-8 July, 2016.

[6] S. Huang, W. Liao,H. Zhang, A. Pi?urica, "Paint Loss Detection in Old Paintings by Sparse Representation Classification",International Traveling Workshop on Interactions Between Sparse Models and Technology 2016, Aalborg, Denmark, 24-26 August, 2016.

[7]H. Zhang, W. He, W. Liao, R. Luo, L. Zhang, A. Pi?urica, "Exploiting the Low-Rank Property of Hyperspectral Imagery: A Technical Overview",IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2016), California, USA, 21-24 August, 2016.

[8] H. Li, H. Shen, Q. Yuan,H. Zhang, L. Zhang, L. Zhang, "Quality Improvement of Hyperspectral Remote Sensing Images: A Technical Overview",IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2016), California, USA, 21-24 August, 2016.

[9] R. Wang, H. C. Li, W. Liao,H. Zhang, A. Pi?urica, "Hyperpsectral Unmixing by Reweighted Low Rank Representation",IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2016), California, USA, 21-24 August, 2016.

[10] H. Zhai,H. Zhang, L. Zhang, P. Li "Squaring Weighted Low-rank Subspace Clustering for Hyperspectral Image Band Selection",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2016),Beijing, China, 10u201315 July, 2016.

[11] W. He,H. Zhang, L. Zhang, "Hyperspectral Unmixing Using Total Variation Regularized Reweighted Sparse Non-Negative Matrix Factorization",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2016),Beijing, China, 10u201315 July, 2016.

[12] H. Chen,H. Zhang, L. Zhang, "Robust Superresolution of Multiangle-Multispectral Remote Sensing Images based on Rank Minimization",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2016),Beijing, China, 10u201315 July, 2016.

[13]H. Zhang, H. Zhai, W. Liao, L. Cao, L. Zhang, A. Pi?urica, "Hyperspectral Image Kernel Sparse Subspace Clustering with Spatial Max Pooling Operation",the 23th International Society for Photogrammetry and Remote Sensing Congress (ISPRS 2016),Prague, Czech, 12u201319 July, 2016.

[14] R. Luo, W. Liao,H. Zhang, L. Zhang, Y. Pi, W. Philips, "Classification of Cloudy Hyperspectral Image and LIDAR Data based on Feature Fusion and Desicion Fusion",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2016),Beijing, China, 10u201315 July, 2016.

[15] J. Li,H. Zhang, L. Zhang, "Efficient Superpixel-Oriented Multi-task Joint Sparse Representation Classification for Hyperspectral imagery",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2015), Milan,Italy, 26u201331 July, 2015.

[16] H. Zhai,H. Zhang, L. Zhang, P. Li, X. Xu, "Spectral-Spatial Clustering of Hyperspectral Remote Sensing Image with Sparse Subspace Clustering Model",IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2015), Tokyo, Japan, 2-5 June, 2015.

[17] W. He,H. Zhang, L. Zhang, H. Shen, "A Noise-Adjusted Iterative Randomized Singular Value Decomposition Method for Hyperspectral Image Denoising",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2014), Quebec,Canada, 13u201318 July, 2014.(2014 IEEE GARSS Student Paper Contest Top 3)

[18] J. Li,H. Zhang, L. Zhang, "Background Joint Sparse Representation for Hyperspectral Image Subpixel Anomaly Detection",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2014), Quebec,Canada, 13u201318 July, 2014.

[19] J. Li,H. Zhang, L. Zhang, "A Nonlinear Regression Classification Algorithm with Small Sample Set for Hyperspectral Image",IEEE International Geoscience and Remote Sensing Symposium (IGRASS 2013), Melbourne, Australia, 21u201326 July, 2013.

[20] X. Xu, Y. Zhong, L. Zhang,H. Zhang, R. Feng, "A Unified Sub-pixel Mapping Model Intergrating Spectral Unmixing for Hyperspectral Imagery",the 5th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2013), Gainesville, Florida, USA, 2013.

[21]H. Zhang, "Hyperspectral image denoising with cubic total variation model",the 22th International Society for Photogrammetry and Remote Sensing Congress (ISPRS 2012), Melbourne, 25-31 August,2012.

[22] J. Li,H. Zhang, Y. Huang, L. Zhang, "Classification for Hyperspectral Imagery Based on Nonlocal Weighted Joint Sparsity Model",the 4th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2012), Shanghai, China, 4-7 June, 2012.

[23]H. Zhang, L. Zhang, H. Shen, P. Li, "A MAP approach for joint image registration, blur identification and super-resolution",the 5th International Conference on Image and Graphics( ICIG 2009), Xian, China, pp. 97-102, 21-24 September, 2009.

中文论文：

[1] 张亚坤，张洪艳，沈焕锋，张良培， "一种基于稀疏表达的遥感影像时空融合方法"，电子科技，vol. 30, no. 11, pp. 56-59，2017.

[2] 帅滔，张洪艳，"基于新型阴影指标的遥感影像阴影检测方法"，电子科技，vol. 29, no. 2, 2016.

[3] 帅滔，张洪艳，张良培，"面向对象的高分辨率遥感影像阴影探测方法"，光子学报，vol. 44, no. 12, 2015.

[4] 姜湾, 沈焕锋, 曾超, 张良培,张洪艳, "Terra卫星MODIS传感器28波段影像的条带噪声去除方法,"武汉大学学报(信息科学版), vol. 39, no. 5, pp.526-530, 2014.

[5]张洪艳，沈焕锋，张良培，李平湘，袁强强，"基于最大后验估计的图像盲超分辨率重建方法"，计算机应用，vol. 31, no. 5, pp. 1209-1213, 2011.

[6]刘瑜，徐爱锋，张洪艳，"GIS数据应用体系框架研究"，测绘与空间地理信息，vol. 34, no. 2, pp. 157-160, 2011.

[7]徐源Z，汪俏珏，沈焕锋，李平湘，张洪艳，"基于刃边法与正则化方法的遥感影像复原"，测绘信息与工程，vol. 35, no. 6, pp. 7-9, 2010.

[8]张洪艳，沈焕锋，张良培，李平湘，"一种保边缘图像超分辨率重建方法"，中国图象图形学报，vol. 14, no. 11, pp. 2255-2261, 2009.

学术专著：

[1] 张良培, 沈焕锋,张洪艳, 袁强强,"图像超分辨率重建", 专著, 科学出版社, ISBN： 978-7-03-035236-1，2012.

软件著作

[1] 黄昕, 张洪艳, 钟燕飞, 张良培, “新型面向对象影像分类与变化检测系统”, 软件登记号: 2012SR004625, 批准时间: 2012-01-20.

[2] 张良培, 罗旭东, 钟燕飞, 张洪艳, “高光谱影像成像光谱分析软件”, 软件登记号: 2015SR071825, 批准时间: 2015-08-13.

教学论文

[1] 张洪艳, "浅谈高校教师素养对课堂教学的影响", 高教学刊, no. 11, pp. 210-211, 2016.

[2] 刘婷婷, 张洪艳, "遥感专业“计算机图形学”教学改革探讨", 大学教育, no. 11, pp. 138-139, 2014.

专利申请

[1] 李家艺, 张洪艳, 张良培, “基于联合稀疏表达的遥感影像多尺度面向对象分类方法”, 专利号: ZL201310628634.7, 授权日: 2016.05.21.

[2] 沈焕锋, 李兴华, 张良培, 张洪艳, “利用多时相数据去除光学遥感影像大面积厚云的方法”, 专利号: ZL 201210551692.X, 授权日: 2015.06.10.

[3] 张洪艳, 张亚坤, 沈焕锋, 袁强强, 张良培, “基于非耦合映射关系的影像超分辨率重建方法及系统”, 申请号: 20161023.1568.3, 申请日: 2016.04.14.

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科研项目

1GF-5高光谱遥感卫星图像混合像元分解方法研究中央高校基本科研业务2042018gf00222018.1~2019.12负责人52融合高光谱和激光雷达数据的城市地物精细化识别国家自然科学基金国际合作交流项目417115307092018.1~2019.12负责人103多时态遥感影像地理信息变化自动提取技术青海省地理空间信息技术与应用重点实验室开放基金QDXS-2017-012017.9~2018.9负责人54基于高光谱影像分析的食品有害物质定量检测研究中央高校基本科研业务费专项资金20162017.1~2018.12负责人205基于遥感影像的土地分类识别系统广西国土局横向项目20172017.6~2017.12负责人696面向超像素的高光谱遥感影像稀疏表达分类湖北省自然科学基金面上项目20162016.1~2017.12负责人37高光谱遥感影像特征学习-地物分类一体化建模国家自然科学基金面上项目415713622016.1~2019.12负责人728高光谱遥感影像混合像元分解高分辨率对地观测重大专项子课题（GF-5）20152015.9~2017.12负责人409多角度高光谱遥感影像超分辨率重建研究国家自然科学基金青年基金612013422013.1~2015.12负责人2410多时相遥感影像超分辨率盲重建研究博士后科学基金2011M5012422011.9~2012.7负责人311顾及区域差异的遥感影像超分辨率重建方法地理信息工程国家测绘局重点实验室开放基金2011282012.1~2012.12负责人212基于压缩感知理论影像融合方法研究中国科学院数字地球重点实验室开放基金2012LDE0172013.1~2014.12负责人313基于压缩感知理论的多源遥感影像空谱融合研究对地观测技术国家测绘局重点实验室开放基金K2013032014.1~2014.12负责人214面向矿区地理国情监测的多源遥感影像时空融合研究国土环境与灾害监测国家测绘地理信息局重点实验室开放基金LEDM2014B012015.1~2016.12负责人215面向农情信息监测的多源遥感影像时空融合研究农业部农业信息技术重点实验室20140062014.10~2015.10负责人216空天地一体化对地观测传感网的理论与方法国家重点基础研究发展计划2011CB7071002011.1~2015.12研究骨干17