黄珺 副教授
黄珺,武汉大学电子信息学院副教授,硕导,2008年于华中科技大学电子与信息工程系获学士学位;2014年于华中科技大学电子与信息工程系获得电路与系统专业博士学位。主要从事红外成像、红外超光谱成像以及布里渊激光雷达系统等方面的研究工作,主持国家自然科学基金2项,中国博士后基金1项,作为骨干成员参与多项航天8358所、中电11所、兵器211所委托的横向课题,发表SCI论文40余篇,申请国家专利26项,授权20项。2013年“高性能红外成像关键技术研究及其应用”获湖北省科技进步一等奖1项,2014年“高帧频、大面阵红外成像关键技术及装备”获教育部技术发明奖二等奖1项。国际期刊Infrared Physics & Technology、IEEE Access、Information Sciences、Applied Optics、JOSA A、Sensors审稿人。
联系方式
Email:junhwong@whu.edu.cn
google学术个人主页:https://scholar.google.com/citations?user=7KE1gqsAAAAJ&hl=zh-CN
教育背景
2008/9–2014/3, 华中科技大学, 电路与系统, 博士
2004/9–2008/6, 华中科技大学, 电子信息工程, 学士
工作经历
2018/1-今,武汉大学,电子信息学院,副教授,硕导
2016/12-2017/12,佐治亚理工学院,School of Electrical and Computer Engineering,访问学者
2014/8-2017/12,武汉大学,电子信息学院,讲师
2014/8-2016/7,武汉大学,博士后,合作导师:李德识
学术奖励
(1)高帧频、大面阵红外成像关键技术及装备,教育部高等学校科学研究优秀成果奖(技术发明)二等奖,2014
(2)高性能红外成像关键技术研究及其应用,湖北省科学技术奖(科技进步奖)一等奖,2013
科研项目
主持项目:
- 国家自然科学基金面上项目,62075169,基于多维异源特征与模糊推理的红外与可见光图像融合方法及应用研究,2021/01-2025/12,59万
- 武汉大学自主科研项目,2042020kf0017,基于全局联合稀疏分解的红外与可见光图像融合方法研究,2020/01-2021/12,12万元
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国家自然科学基金青年基金,61605146,面向傅里叶红外成像光谱仪干涉数据立方的场景非均匀性校正方法,2017-2019,19万
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中国博士后科学基金,2015M572194,基于傅里叶成像光谱仪的海面温度遥感信号处理方法研究,2015-2016,5万
参与项目:
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国家自然科学基金面上项目,61275098,红外超光谱谱指纹检测和识别海洋溢油污染方法研究,2013-2016
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国家自然科学基金青年基金,61108074,实时获取高精度海水布里渊频谱的信号处理方法研究,2012-2014
授权专利
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基于局部线性迁移的非刚性变换图像特征匹配方法及系统,申请号:ZL 201510801246.3
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基于局部线性迁移和刚性模型的图像特征匹配方法及系统,申请号:ZL 201510807463.3
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基于局部线性迁移和仿射变换的图像特征匹配方法及系统,申请号:ZL 201510799813.6
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一种基于边界投影最优梯度的高光谱非线性解混方法,申请号:ZL 201510700049.2
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基于特征索引的超光谱匹配方法及系统,专利号:ZL 201410627713.0
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一种基于鲁棒低秩张量的高光谱图像去噪方法,专利号:ZL 201510521057.0
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用于光谱图像数据降维的邻居点搜索方法及系统,专利号:ZL 201410468127.6
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基于空间相关性的高光谱数据降噪方法及系统,专利号:ZL 201410821313.3
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基于边缘提取的红外图像直方图增强方法,专利号:ZL 201410834788.6
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一种基于噪声识别的红外图像降噪方法,专利号:ZL 201510004744.5
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基于光谱抽样直方图的超光谱降维匹配方法及系统,专利号:ZL 201410584276.9
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一种面向超光谱数据库的小波去噪算法,专利号:ZL 201410510422.3
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用于目标识别的红外超光谱信号处理方法、处理机及系统,专利号:ZL 201410700672.3
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法布里珀罗干涉圆环图像处理方法,专利号:ZL 201310285640.7
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基于双平台直方图的红外图像自适应增强方法,专利号:ZL201110370520.8
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扫描型红外成像系统的非均匀校正方法,专利号:ZL201110312154.0
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多气象参数同步测量激光雷达,专利号:ZL201120525536.7
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一种通过长短积分控制实现红外图像增强的方法,专利号:ZL201010502552.4
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适用于高帧率大面阵红外探测器的实时红外图像处理系统,专利号:ZL201010502547.3
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基于频谱特征信号的多气象参数同步测量方法及激光雷达,专利号:ZL201110178286.9
学术论文
- Wu M , Ma Y , Huang J , et al. A new patch-based two-scale decomposition for infrared and visible image fusion[J]. Infrared Physics & Technology, 2020:103362.
- Huang J , Le Z , Ma Y , et al. A generative adversarial network with adaptive constraints for multi-focus image fusion[J]. Neural Computing and Applications, 2020:1-11.
- Wu L, Ma Y, Fan F, Wu M, Huang J*, et al. A Double-Neighborhood Gradient Method for Infrared Small Target Detection[J]. IEEE Geoscience and Remote Sensing Letters, 2020.
- Wang Y, Mei X, Ma Y, Huang J*, et al. Learning to find reliable correspondences with local neighborhood consensus[J]. Neurocomputing, 2020.
- 周怡,马佳义,黄珺. 基于互导滤波和显著性映射的红外可见光图像融合[J]. 遥感技术与应用,2020,35(3):1 – 11.
- Wu M, Ma Y, Fan F, Mei X, Huang J*, et al. Infrared and visible image fusion via joint convolutional sparse representation[J]. JOSA A, 2020, 37(7): 1105-1115.
- Ma Y, Fan G, Jin Q, Huang J*. et al. Hyperspectral Anomaly Detection via Integration of Feature Extraction and Background Purification[J]. IEEE Geoscience and Remote Sensing Letters, 2020.
- Jun Huang, Zhuliang Le, Yong Ma, et al. MGMDcGAN: Medical Image Fusion Using Multi-Generator Multi-Discriminator Conditional Generative Adversarial Network[J]. IEEE Access, 2020, 8(1): 55145-55157.
- Xu Han, Fan Fan, Zhang Hao, Le Zhuliang, Huang Jun*, A Deep Model for Multi-Focus Image Fusion Based on Gradients and Connected Regions[J]. IEEE Access, 2020, 8(1): 26316-263278.
- Ma Y, Jin Q, Mei X, et al. Hyperspectral Unmixing with Gaussian Mixture Model and Low-Rank Representation[J]. Remote Sensing, 2019, 11(8): 911.
- Jin Q, Ma Y, Pan E, et al. Hyperspectral Unmixing with Gaussian Mixture Model and Spatial Group Sparsity[J]. Remote Sensing, 2019, 11(20): 2434.
- Mei X, Pan E, Ma Y, et al. Spectral-Spatial Attention Networks for Hyperspectral Image Classification[J]. Remote Sensing, 2019, 11(8): 963.
- Ma Y, Wang Y, Mei X, et al. Visible/Infrared Combined 3D Reconstruction Scheme Based on Nonrigid Registration of Multi-Modality Images With Mixed Features[J]. IEEE Access, 2019, 7: 19199-19211.
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Wang J, Chen J, Xu H, Zhang S, Mei X, Huang J, et al. Gaussian field estimator with manifold regularization for retinal image registration[J]. Signal Processing, 2019, 157: 225-235.
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Du Q, Xu H, Ma Y, Huang J, et al. Fusing Infrared and Visible Images of Different Resolutions via Total Variation Model[J]. Sensors, 2018, 18(11): 3827.
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Fan F, Ma Y, Huang J, et al. Infrared Image Enhancement based on Saliency Weight with Adaptive Threshold[C]//2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP). IEEE, 2018: 225-230.
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Mei X, Ma Y, Li C, Fan F, Huang J, et al. Robust GBM hyperspectral image unmixing with superpixel segmentation based low rank and sparse representation[J]. Neurocomputing, 2018, 275: 2783-2797.
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Du Q, Fan A, Ma Y, Fan F, Huang J, et al. Infrared and Visible Image Registration Based on Scale-Invariant PIIFD Feature and Locality Preserving Matching[J]. IEEE Access, 2018, 6: 64107-64121.
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Huang J, Ma Y, Zhang Y, et al. Infrared image enhancement algorithm based on adaptive histogram segmentation[J]. Applied optics, 2017, 56(35): 9686-9697.
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Xiaoye Zhang, Yong Ma, Fan Fan, Ying Zhang, and Jun Huang*. Infrared and visible image fusion via saliency analysis and local edge-preserving multi-scale decomposition[J]. JOSA A, 2017, 34(8): 1400-1410.
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Huang J, Ma Y, Mei X, et al. A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA[J]. Infrared Physics & Technology, 2016, 79: 68-73.
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Liu Z, Ma Y, Huang J*, et al. A registration based nonuniformity correction algorithm for infrared line scanner[J]. Infrared Physics & Technology, 2016, 76: 667-675.
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Ma J, Chen C, Li C, Huang, J.* Infrared and visible image fusion via gradient transfer and total variation minimization[J]. Information Fusion, 2016, 31: 100-109.
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Huang J, Ma Y, Fan F, et al. “A scene-based nonuniformity correction algorithm based on fuzzy logic.” Optical Review 22.4 (2015): 614-622.
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Fan F, Ma Y, Huang J,* et al. “A combined temporal and spatial deghosting technique in scene based nonuniformity correction.” Infrared Physics & Technology 71 (2015): 408-415.
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Huang, J., Ma, Y., Zhou, B., et al. “Processing method of spectral measurement using FP etalon and ICCD.” Optics express 20.17 (2012): 18568-18578.
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Liang, K., Ma, Y., Huang, J.*, et al. “Precise measurement of Brillouin scattering spectrum in the ocean using F–P etalon and ICCD.” Applied Physics B 105.2 (2011): 421-425.
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Li C, Ma Y, Mei X, Fan F, Huang J, et al. Sparse Unmixing of Hyperspectral Data with Noise Level Estimation[J]. Remote Sensing, 2017, 9(11): 1166.
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Fan F, Ma Y, Li C, Mei X, Huang J, et al. Hyperspectral image denoising with superpixel segmentation and low-rank representation[J]. Information Sciences, 2017, 397: 48-68.
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Liu C, Ma J, Ma Y, Huang J et al. Retinal image registration via feature-guided Gaussian mixture model[J]. JOSA A, 2016, 33(7): 1267-1276.
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Li C, Ma Y, Huang J, et al. Gbm-based unmixing of hyperspectral data using bound projected optimal gradient method[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(7): 952-956.
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J. Han, Y. Ma, J. Huang, X. Mei and J. Ma, “An Infrared Small Target Detecting Algorithm Based on Human Visual System,” in IEEE Geoscience and Remote Sensing Letters, 13.3(2016), 452-456
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Zhou, B., Fan, Q., Ma, Y., Yao, Y., Li, H., Huang, J., & Liang, K. Experimental analysis on the rapid measurement of a high precision Brillouin scattering spectrum in water using a Fabry–Pérot etalon[J]. Laser Physics Letters, 2016, 13(5): 055701.
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Li C, Ma Y, Huang J, et al. “Hyperspectral image denoising using the robust low-rank tensor recovery.” JOSA A 32.9 (2015): 1604-1612.
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Mei, X., Ma, Y., Li, C., Fan, F., Huang, J., & Ma, J. “A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching.” Sensors 15.7 (2015): 15868-15887.
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Mei, X., Ma, Y., Fan, F., Li, C., Liu, C., Huang, J., & Ma, J. Infrared ultraspectral signature classification based on a restricted Boltzmann machine with sparse and prior constraints[J]. International Journal of Remote Sensing, 2015, 36(18): 4724-4747.
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Ma, Y., Li, H., Gu, Z., Ubachs, W., Yu, Y., Huang, J., et al. “Analysis of Rayleigh-Brillouin spectral profiles and Brillouin shifts in nitrogen gas and air.” Optics express 22.2 (2014): 2092-2104.
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Ma, Y., Yu, Y., Li, H., Huang, J., et al. “Accurate measurement of high resolution spectrum obtained by F–P etalon and ICCD.” Applied Physics B 116.3 (2014): 575-584.
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Ma, Y., Li, H., Yu, Y., Yao, Y., Fang, Y., Zhou, B., Huang, J. , et al. “Experimental analysis on calibration of instrument broadening in a lidar system with Fabry–Perot etalon.” Journal of Modern Optics 60.21 (2013): 1967-1975.
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Liang, K., Ma, Y., Yu, Y., Huang, J., et al. “Research on simultaneous measurement of ocean temperature and salinity using Brillouin shift and linewidth.” Optical Engineering 51.6 (2012): 066002-1.
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Yu, Y., Ma, Y., Li, H., Huang, J., et al. “Simulation of simultaneously obtaining ocean temperature and salinity using dual-wavelength Brillouin lidar.” Laser Physics Letters 11.3 (2014): 036001.