個(gè)人簡(jiǎn)介
教育經(jīng)歷2005/09-2010/06，武漢大學(xué)，測(cè)繪遙感信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室，攝影測(cè)量與遙感專(zhuān)業(yè)，博士2001/09-2005/06，武漢大學(xué)，資源與環(huán)境科學(xué)學(xué)院，地理信息系統(tǒng)專(zhuān)業(yè)，學(xué)士工作經(jīng)歷2016/12-至今，武漢大學(xué)測(cè)繪遙感信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室，破格教授2016/09-2016/11，葡萄牙里斯本大學(xué)，訪(fǎng)問(wèn)學(xué)者2015/12-2016/08，比利時(shí)根特大學(xué)，訪(fǎng)問(wèn)學(xué)者2013/12-2016/11，武漢大學(xué)測(cè)繪遙感信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室，副研究員2010/08-2013/11，武漢大學(xué)測(cè)繪遙感信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室，講師學(xué)術(shù)兼職Computers & Geosciences期刊副主編Geosciences期刊編委IEEE資深會(huì)員(IEEE Senior Member)2015 IEEEWHISPERS、2016 IGARSS Session Chair38個(gè)國(guó)際學(xué)術(shù)期刊和多個(gè)國(guó)內(nèi)核心期刊審稿員榮譽(yù)獎(jiǎng)勵(lì)
2016年，“創(chuàng)青春”全國(guó)大學(xué)生創(chuàng)業(yè)大賽金獎(jiǎng)指導(dǎo)老師2015年，國(guó)家留學(xué)基金委首屆“未來(lái)科學(xué)家”2014年，IEEE地球科學(xué)與遙感學(xué)會(huì)數(shù)據(jù)融合大賽影像分類(lèi)賽第三名2014年，IEEE國(guó)際地球科學(xué)與遙感大會(huì)學(xué)生論文競(jìng)賽第三名指導(dǎo)老師2013年，武漢大學(xué)第四批“珞珈青年學(xué)者”學(xué)術(shù)研究
期刊論文（按時(shí)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.
[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(huì)議論文（按時(shí)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(dá)的遙感影像時(shí)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(biāo)的遙感影像陰影檢測(cè)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(cè)方法"，光子學(xué)報(bào)，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(xué)學(xué)報(bào)(信息科學(xué)版), vol. 39, no. 5, pp.526-530, 2014.
[5]張洪艷，沈煥鋒，張良培，李平湘，袁強(qiáng)強(qiáng)，"基于最大后驗(yàn)估計(jì)的圖像盲超分辨率重建方法"，計(jì)算機(jī)應(yīng)用，vol. 31, no. 5, pp. 1209-1213, 2011.
[6]劉瑜，徐愛(ài)鋒，張洪艷，"GIS數(shù)據(jù)應(yīng)用體系框架研究"，測(cè)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(fù)原"，測(cè)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(guó)圖象圖形學(xué)報(bào)，vol. 14, no. 11, pp. 2255-2261, 2009.
學(xué)術(shù)專(zhuān)著：[1] 張良培, 沈煥鋒,張洪艷, 袁強(qiáng)強(qiáng),"圖像超分辨率重建", 專(zhuān)著, 科學(xué)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?lèi)與變化檢測(cè)系統(tǒng)”, 軟件登記號(hào): 2012SR004625, 批準(zhǔn)時(shí)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(hào): 2015SR071825, 批準(zhǔn)時(shí)間: 2015-08-13.
教學(xué)論文[1] 張洪艷, "淺談高校教師素養(yǎng)對(duì)課堂教學(xué)的影響", 高教學(xué)刊, no. 11, pp. 210-211, 2016.
[2] 劉婷婷, 張洪艷, "遙感專(zhuān)業(yè)“計(jì)算機(jī)圖形學(xué)”教學(xué)改革探討", 大學(xué)教育, no. 11, pp. 138-139, 2014.
專(zhuān)利申請(qǐng)[1] 李家藝, 張洪艷, 張良培, “基于聯(lián)合稀疏表達(dá)的遙感影像多尺度面向?qū)ο蠓诸?lèi)方法”, 專(zhuān)利號(hào): 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(shí)相數(shù)據(jù)去除光學(xué)遙感影像大面積厚云的方法”, 專(zhuān)利號(hào): ZL 201210551692.X, 授權(quán)日: 2015.06.10.
[3] 張洪艷, 張亞坤, 沈煥鋒, 袁強(qiáng)強(qiáng), 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(qǐng)?zhí)? 20161023.1568.3, 申請(qǐng)日: 2016.04.14.
對(duì)以上論文或其它內(nèi)容感興趣的學(xué)者朋友歡迎到張洪艷老師個(gè)人網(wǎng)站上查詢(xún)或下載。
科研項(xiàng)目
| 1 | GF-5高光譜遙感衛(wèi)星圖像混合像元分解方法研究 | 中央高校基本科研業(yè)務(wù) | 2042018gf0022 | 2018.1~2019.12 | 負(fù)責(zé)人 | 5 |
| 2 | 融合高光譜和激光雷達(dá)數(shù)據(jù)的城市地物精細(xì)化識(shí)別 | 國(guó)家自然科學(xué)基金國(guó)際合作交流項(xiàng)目 | 41711530709 | 2018.1~2019.12 | 負(fù)責(zé)人 | 10 |
| 3 | 多時(shí)態(tài)遙感影像地理信息變化自動(dòng)提取技術(shù) | 青海省地理空間信息技術(shù)與應(yīng)用重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金 | QDXS-2017-01 | 2017.9~2018.9 | 負(fù)責(zé)人 | 5 |
| 4 | 基于高光譜影像分析的食品有害物質(zhì)定量檢測(cè)研究 | 中央高�；究蒲袠I(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金 | 2016 | 2017.1~2018.12 | 負(fù)責(zé)人 | 20 |
| 5 | 基于遙感影像的土地分類(lèi)識(shí)別系統(tǒng) | 廣西國(guó)土局橫向項(xiàng)目 | 2017 | 2017.6~2017.12 | 負(fù)責(zé)人 | 69 |
| 6 | 面向超像素的高光譜遙感影像稀疏表達(dá)分類(lèi) | 湖北省自然科學(xué)基金面上項(xiàng)目 | 2016 | 2016.1~2017.12 | 負(fù)責(zé)人 | 3 |
| 7 | 高光譜遙感影像特征學(xué)習(xí)-地物分類(lèi)一體化建模 | 國(guó)家自然科學(xué)基金面上項(xiàng)目 | 41571362 | 2016.1~2019.12 | 負(fù)責(zé)人 | 72 |
| 8 | 高光譜遙感影像混合像元分解 | 高分辨率對(duì)地觀(guān)測(cè)重大專(zhuān)項(xiàng)子課題（GF-5） | 2015 | 2015.9~2017.12 | 負(fù)責(zé)人 | 40 |
| 9 | 多角度高光譜遙感影像超分辨率重建研究 | 國(guó)家自然科學(xué)基金青年基金 | 61201342 | 2013.1~2015.12 | 負(fù)責(zé)人 | 24 |
| 10 | 多時(shí)相遙感影像超分辨率盲重建研究 | 博士后科學(xué)基金 | 2011M501242 | 2011.9~2012.7 | 負(fù)責(zé)人 | 3 |
| 11 | 顧及區(qū)域差異的遙感影像超分辨率重建方法 | 地理信息工程國(guó)家測(cè)繪局重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金 | 201128 | 2012.1~2012.12 | 負(fù)責(zé)人 | 2 |
| 12 | 基于壓縮感知理論影像融合方法研究 | 中國(guó)科學(xué)院數(shù)字地球重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金 | 2012LDE017 | 2013.1~2014.12 | 負(fù)責(zé)人 | 3 |
| 13 | 基于壓縮感知理論的多源遙感影像空譜融合研究 | 對(duì)地觀(guān)測(cè)技術(shù)國(guó)家測(cè)繪局重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金 | K201303 | 2014.1~2014.12 | 負(fù)責(zé)人 | 2 |
| 14 | 面向礦區(qū)地理國(guó)情監(jiān)測(cè)的多源遙感影像時(shí)空融合研究 | 國(guó)土環(huán)境與災(zāi)害監(jiān)測(cè)國(guó)家測(cè)繪地理信息局重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金 | LEDM2014B01 | 2015.1~2016.12 | 負(fù)責(zé)人 | 2 |
| 15 | 面向農(nóng)情信息監(jiān)測(cè)的多源遙感影像時(shí)空融合研究 | 農(nóng)業(yè)部農(nóng)業(yè)信息技術(shù)重點(diǎn)實(shí)驗(yàn)室 | 2014006 | 2014.10~2015.10 | 負(fù)責(zé)人 | 2 |
| 16 | 空天地一體化對(duì)地觀(guān)測(cè)傳感網(wǎng)的理論與方法 | 國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃 | 2011CB707100 | 2011.1~2015.12 | 研究骨干 | 17 |
