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  • 張洪艷

    張洪艷(武大教授)

    張洪艷教授,男,1983年生,博士畢業(yè)于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(nóng)業(yè)遙感和機器學習等方向的研究工作。

    張洪艷曾榮獲武漢大學“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計劃”等人才計劃。在國內(nèi)外學術(shù)期刊和會議上發(fā)表論文85余篇,其中SCI期刊論文47篇,EI檢索論文19篇,學術(shù)專著1部,申請國家發(fā)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。先后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。

    張教授先后榮獲2017年國家測繪科技進步獎一等獎(排名第二),2016年“創(chuàng)青春”全國大學生創(chuàng)業(yè)大賽金獎指導老師,IEEE地球科學與遙感學會2014年度數(shù)據(jù)融合大賽第三名(全球共40余個參賽團體),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余名參賽者)。


    個人簡介

    教育經(jīng)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(yè),博士2001/09-2005/06,武漢大學,資源與環(huán)境科學學院,地理信息系統(tǒng)專業(yè),學士工作經(jīng)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(shù)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 Chair38個國際學術(shù)期刊和多個國內(nèi)核心期刊審稿員

    榮譽獎勵

    2016年,“創(chuàng)青春”全國大學生創(chuàng)業(yè)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(shù)據(jù)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(shù)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. 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.

    張洪艷

    [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.

    會議論文(按時間排列):

    [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.

    中文論文:

    [1] 張亞坤,張洪艷,沈煥鋒,張良培, "一種基于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,"基于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?qū)ο蟮母叻直媛蔬b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(wèi)星MODIS傳感器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,"基于最大后驗估計的圖像盲超分辨率重建方法",計算機應(yīng)用,vol. 31, no. 5, pp. 1209-1213, 2011.

    [6]劉瑜,徐愛鋒,張洪艷,"GIS數(shù)據(jù)應(yīng)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,汪俏玨,沈煥鋒,李平湘,張洪艷,"基于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,"一種保邊緣圖像超分辨率重建方法",中國圖象圖形學報,vol. 14, no. 11, pp. 2255-2261, 2009.

    學術(shù)專著:

    [1] 張良培, 沈煥鋒,張洪艷, 袁強強,"圖像超分辨率重建", 專著, 科學出版社, ISBN: 978-7-03-035236-1,2012.

    軟件著作

    [1] 黃昕, 張洪艷, 鐘燕飛, 張良培, “新型面向?qū)ο笥跋穹诸惻c變化檢測系統(tǒng)”, 軟件登記號: 2012SR004625, 批準時間: 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件”, 軟件登記號: 2015SR071825, 批準時間: 2015-08-13.

    教學論文

    [1] 張洪艷, "淺談高校教師素養(yǎng)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(yè)“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, “基于聯(lián)合稀疏表達的遙感影像多尺度面向?qū)ο蠓诸惙椒ā? 專利號: ZL201310628634.7, 授權(quán)日: 2016.05.21.

    [2] 沈煥鋒, 李興華, 張良培, 張洪艷, “利用多時相數(shù)據(jù)去除光學遙感影像大面積厚云的方法”, 專利號: ZL 201210551692.X, 授權(quán)日: 2015.06.10.

    [3] 張洪艷, 張亞坤, 沈煥鋒, 袁強強, 張良培, “基于非耦合映射關(guān)系的影像超分辨率重建方法及系統(tǒng)”, 申請?zhí)? 20161023.1568.3, 申請日: 2016.04.14.

    對以上論文或其它內(nèi)容感興趣的學者朋友歡迎到張洪艷老師個人網(wǎng)站上查詢或下載。

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