張洪艷(武漢大學教授)

張洪艷教授，男，1983年生，博士畢業於武漢大學測繪遙感信息工程國家重點實驗室，目前擔任武漢大學測繪遙感信息工程國家重點實驗室教授、博士生導師，主要從事高光譜遙感信息處理、農業遙感和機器學習等方向的研究工作。

張洪艷教授曾榮獲教育部“長江學者獎勵計畫”青年學者，武漢大學“珞珈青年學者”，國家留學基金委首批“未來科學家”等榮譽稱號，武漢大學“351計畫”等人才計畫。在國內外學術期刊和會議上發表論文85餘篇，其中SCI期刊論文47篇，EI檢索論文19篇，學術專著1部，申請國家發明專利3項，論文共被引用2000多次，ESI熱點論文2篇， ESI高被引論文4篇，Elsevier年度熱門論文1篇。先後主持自然科學基金項目4項、湖北省自然科學基金等省部級科研項目2項。

張教授先後榮獲2017年國家測繪科技進步獎一等獎(排名第二)，2016年“創青春”全國大學生創業大賽金獎指導老師，IEEE地球科學與遙感學會2014年度數據融合大賽第三名(全球共40餘個參賽團體)，2014年IEEE國際地球科學與遙感大會學生論文競賽第三名指導老師（全球共80餘名參賽者）。張教授為IEEE Senior Member，應邀擔任Computers & Geosciences期刊副主編、Geosciences期刊編委和IEEE IGARSS、IEEE WHISPERS等國際會議的分會主席，擔任38個國際SCI期刊的審稿員。

基本介紹

• 中文名：張洪艷
• 外文名：Hongyan Zhang
• 別名：Gamma老師
• 國籍：中國
• 民族：漢族
• 出生地：河南省開封市
• 出生日期：1983年12月18日
• 職業：教授，博士生導師
• 畢業院校：武漢大學 測繪遙感信息工程國家重點實驗室
• 信仰：共產主義
• 主要成就：“長江學者獎勵計畫”青年學者，珞珈青年學者，未來科學家
• 代表作品：圖像超分重建

個人簡介

• 教育經歷
• 2005/09-2010/06，武漢大學，測繪遙感信息工程國家重點實驗室，攝影測量與遙感專業，博士
• 2001/09-2005/06，武漢大學，資源與環境科學學院，地理信息系統專業，學士
• 工作經歷
• 2016/12-至今，武漢大學測繪遙感信息工程國家重點實驗室，破格教授
• 2016/09-2016/11，葡萄牙里斯本大學，訪問學者
• 2015/12-2016/08，比利時根特大學，訪問學者
• 2013/12-2016/11，武漢大學測繪遙感信息工程國家重點實驗室，副研究員
• 2010/08-2013/11，武漢大學測繪遙感信息工程國家重點實驗室，講師
• 學術兼職
• Computers & Geosciences期刊副主編
• Geosciences期刊編委
• IEEE資深會員(IEEE Senior Member)
• 2015 IEEEWHISPERS、2016 IGARSS Session Chair
• 38個國際學術期刊和多個國核心心期刊審稿員

榮譽獎勵

• 2017年，教育部“長江學者獎勵計畫”青年學者
• 2016年，“創青春”全國大學生創業大賽金獎指導老師
• 2015年，國家留學基金委首屆“未來科學家”
• 2014年，IEEE地球科學與遙感學會數據融合大賽影像分類賽第三名
• 2014年，IEEE國際地球科學與遙感大會學生論文競賽第三名指導老師
• 2013年，武漢大學第四批“珞珈青年學者”

學術研究

• 期刊論文（按時間排列）：

[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. Pižurica, "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. 389–408, 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. 3672–3684, 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. 901–911. 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.

• 會議論文（按時間排列）:

[1] S. Huang,H. Zhang, A. Pižurica, "Robust Joint Sparsity Model for Hyperspectral Image Classification",International Conference on Image Processing (ICIP 2017), Beijing, China, 17–20 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, 23–27 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. Pižurica, "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. Pižurica, "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. Pižurica, "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. Pižurica, "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, 10–15 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, 10–15 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, 10–15 July, 2016.

[13]H. Zhang, H. Zhai, W. Liao, L. Cao, L. Zhang, A. Pižurica, "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, 12–19 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, 10–15 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, 26–31 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, 13–18 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, 13–18 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, 21–26 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.

• 中文論文：

[1] 張亞坤，張洪艷，沈煥鋒，張良培， "一種基於稀疏表達的遙感影像時空融合方法"，電子科技，vol. 30, no. 11, pp. 56-59，2017.

[2] 帥滔，張洪艷，"基於新型陰影指標的遙感影像陰影檢測方法"，電子科技，vol. 29, no. 2, 2016.

[3] 帥滔，張洪艷，張良培，"面向對象的高解析度遙感影像陰影探測方法"，光子學報，vol. 44, no. 12, 2015.

[4] 姜灣, 沈煥鋒, 曾超, 張良培,張洪艷, "Terra衛星MODIS感測器28波段影像的條帶噪聲去除方法,"武漢大學學報(信息科學版), vol. 39, no. 5, pp.526-530, 2014.

[5]張洪艷，沈煥鋒，張良培，李平湘，袁強強，"基於最大後驗估計的圖像盲超解析度重建方法"，計算機套用，vol. 31, no. 5, pp. 1209-1213, 2011.

[6]劉瑜，徐愛鋒，張洪艷，"GIS數據套用體系框架研究"，測繪與空間地理信息，vol. 34, no. 2, pp. 157-160, 2011.

[7]徐源璟，汪俏珏，沈煥鋒，李平湘，張洪艷，"基於刃邊法與正則化方法的遙感影像復原"，測繪信息與工程，vol. 35, no. 6, pp. 7-9, 2010.

[8]張洪艷，沈煥鋒，張良培，李平湘，"一種保邊緣圖像超解析度重建方法"，中國圖象圖形學報，vol. 14, no. 11, pp. 2255-2261, 2009.

• 學術專著：

[1] 張良培, 沈煥鋒,張洪艷, 袁強強,"圖像超解析度重建", 專著, 科學出版社, ISBN： 978-7-03-035236-1，2012.

• 軟體著作

[1] 黃昕, 張洪艷, 鐘燕飛, 張良培, “新型面向對象影像分類與變化檢測系統”, 軟體登記號: 2012SR004625, 批准時間: 2012-01-20.

[2] 張良培, 羅旭東, 鐘燕飛, 張洪艷, “高光譜影像成像光譜分析軟體”, 軟體登記號: 2015SR071825, 批准時間: 2015-08-13.

• 教學論文

[1] 張洪艷, "淺談高校教師素養對課堂教學的影響", 高教學刊, no. 11, pp. 210-211, 2016.

[2] 劉婷婷, 張洪艷, "遙感專業“計算機圖形學”教學改革探討", 大學教育, no. 11, pp. 138-139, 2014.

• 專利申請

[1] 李家藝, 張洪艷, 張良培, “基於聯合稀疏表達的遙感影像多尺度面向對象分類方法”, 專利號: ZL201310628634.7, 授權日: 2016.05.21.

[2] 沈煥鋒, 李興華, 張良培, 張洪艷, “利用多時相數據去除光學遙感影像大面積厚雲的方法”, 專利號: ZL 201210551692.X, 授權日: 2015.06.10.

[3] 張洪艷, 張亞坤, 沈煥鋒, 袁強強, 張良培, “基於非耦合映射關係的影像超解析度重建方法及系統”, 申請號: 20161023.1568.3, 申請日: 2016.04.14.

對以上論文或其它內容感興趣的學者朋友歡迎到張洪艷老師個人網站上查詢或下載。

科研項目

1	GF-5高光譜遙感衛星圖像混合像元分解方法研究	中央高校基本科研業務	2042018gf0022	2018.1~2019.12	負責人	5
2	融合高光譜和雷射雷達數據的城市地物精細化識別	國家自然科學基金國際合作交流項目	41711530709	2018.1~2019.12	負責人	10
3	多時態遙感影像地理信息變化自動提取技術	青海省地理空間信息技術與套用重點實驗室開放基金	QDXS-2017-01	2017.9~2018.9	負責人	5
4	基於高光譜影像分析的食品有害物質定量檢測研究	中央高校基本科研業務費專項資金	2016	2017.1~2018.12	負責人	20
5	基於遙感影像的土地分類識別系統	廣西國土局橫向項目	2017	2017.6~2017.12	負責人	69
6	面向超像素的高光譜遙感影像稀疏表達分類	湖北省自然科學基金面上項目	2016	2016.1~2017.12	負責人	3
7	高光譜遙感影像特徵學習-地物分類一體化建模	國家自然科學基金面上項目	41571362	2016.1~2019.12	負責人	72
8	高光譜遙感影像混合像元分解	高解析度對地觀測重大專項子課題（GF-5）	2015	2015.9~2017.12	負責人	40
9	多角度高光譜遙感影像超解析度重建研究	國家自然科學基金青年基金	61201342	2013.1~2015.12	負責人	24
10	多時相遙感影像超解析度盲重建研究	博士後科學基金	2011M501242	2011.9~2012.7	負責人	3
11	顧及區域差異的遙感影像超解析度重建方法	地理信息工程國家測繪局重點實驗室開放基金	201128	2012.1~2012.12	負責人	2
12	基於壓縮感知理論影像融合方法研究	中國科學院數字地球重點實驗室開放基金	2012LDE017	2013.1~2014.12	負責人	3
13	基於壓縮感知理論的多源遙感影像空譜融合研究	對地觀測技術國家測繪局重點實驗室開放基金	K201303	2014.1~2014.12	負責人	2
14	面向礦區地理國情監測的多源遙感影像時空融合研究	國土環境與災害監測國家測繪地理信息局重點實驗室開放基金	LEDM2014B01	2015.1~2016.12	負責人	2
15	面向農情信息監測的多源遙感影像時空融合研究	農業部農業信息技術重點實驗室	2014006	2014.10~2015.10	負責人	2
16	空天地一體化對地觀測感測網的理論與方法	國家重點基礎研究發展計畫	2011CB707100	2011.1~2015.12	研究骨幹	17