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吕小光
2021-11-09 10:17     (点击: )
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吕小光:教授,硕士生导师

邮箱:xiaoguanglv@.jou.edu.cn

研究方向:数值代数、图像处理

个人履历

吕小光,1979年6月生,湖北黄冈人,博士,教授。电子科技大学博士研究生,南京师范大学博士后,加州大学洛杉矶分校访问学者,香港浸会大学客座研究员,江苏省计算数学学会常务理事,连云港市数学会理事长、连云港市全民健康信息化专家委员会副主任,连云港市科协委员,校重点学科建设带头人,江苏省高校“青蓝工程”优秀青年骨干教师培养对象,连云港市“521高层次人才培养工程”第二层次培养对象,连云港市“海燕计划”培养对象。

从事大规模结构系统高性能算法和预处理技术及在数字图像处理中的应用研究,并已经取得了一系列成果,发表学术论文50余篇,其中SCI检索论文46篇、EI检索论文6篇,授权发明专利1项;主持国家自然科学基金项目2项,省自然科学基金项目2项,国家博士后基金项目1项,省博士后基金项目1项,主研国家自然科学基金3项、国家973课题项目1项、省自然科学基金项目2项、省科技支撑重大项目1项和省应用基础研究课题1项;获得省科技进步一等奖1项、省教育科学自然科学研究成果二等奖1项、连云港市青年科技奖、连云港市自然科学优秀学术成果二等奖和三等奖各1项、校级优秀教学成果一等奖2项。

承担项目

1.国家自然科学基金委员会,自然科学基金面上项目,基于非凸优化的图像平滑和纹理提取问题研究,2022-01至2025-12,主持。

2.江苏省科学技术厅,自然科学基金面上项目,图像盲复原问题的高性能算法研究,2018-07至2021-06,主持。

3.国家自然科学基金委员会,自然科学基金青年项目,非凸优化及稀疏相似性与图像恢复问题研究,2015-01至2017-12,主持。

4.江苏省科学技术厅,自然科学基金面上项目,基于成像原理的数字图像复原算法研究,2013-07至2016-06,主持。

学术及科研成果

1.水下图像评价及图像增强系统,江苏省教育科学研究成果奖,2018.08,江苏省教育厅,二等奖,4/7。

2.基于重叠组稀疏全变分方法的泊松噪声图像复原,连云港市自然科学优秀学术成果奖, 2018.12,连云港市人民政府,二等奖,1/3。

3.大规模代数系统新型快速算法及信息科学的交叉研究,四川省科技进步奖,一等奖,四川省,2013,7/10。

 

论文及专著

[1] Xiao-Guang Lv, Jun Liu, Fang Li and Xuan-Liang Yao, Blind motion deconvolution for binary images, Journal of Computational and Applied Mathematics, 2021, 393, 113500.(

[2] Xiao-Guang Lv, Fang Li, Jun Liu and Sheng-Tai Lu, A patch-based low-rank minimization approach for speckle noise reduction in ultrasound images, Advances in Applied Mathematics and Mechanics, 2021.

[3] Kyongson Jon, Jun Liu, Xiao-Guang Lv and Wensheng Zhu, Poisson noisy image restoration via overlapping group sparse and nonconvex second-order total variation priors, PLOS ONE, 2021.

[4] Jing Yu, Fang Li and Xiao-Guang Lv, Contrast preserving decolorization based on the weighted normalized L1 norm, Multimedia Tools and applications, 2021, 80: 31753-31782.

[5] Fang Li, Ya-Min Ru and Xiao-Guang Lv, Patch-based weighted SCAD prior for Rician noise removal, Journal of Scientific Computing, 2021.

[6] Xiao-Guang Lv, Fang Li, An iterative decoupled method with weighted nuclear norm minimization for image restoration, International Journal of Computer Mathematics, 2020, 97(3): 602-623.

[7] Chang-Qing Yang, Xiao-Guang Lv, Generalized Jacobi spectral Galerkin method for fractional pantograph differential equation, Mathematical Methods in the Applied Sciences, 2020, 44(1): 153-165.

[8] Jian-Hua Hou, Chang-Qing Yang and Xiao-Guang Lv, Jacobi Collocation Methods for Solving the Fractional Bagley-Torvik Equation, IAENG International Journal of Applied Mathematics, 2020, 50:1, IJAM_50_1_17.

[9] Chang-Qing Yang, Jian-Hua Hou, Xiao-Guang Lv, Jacobi spectral collocation method for solving fractional pantograph delay differential equations, Engineering with Computers, 2020, https://doi.org/10.1007/s00366-020-01193-7.

[10] Zhihao Gu, Fang Li, Xiao-Guang Lv, A detail preserving variational model for image retinex, Applied Mathematical Modelling, 2019, 68: 643–661.

[11] Fang Li and Xiao-Guang Lv*, Zi-Wei Deng, Regularized iterative weiner filter method for blind image deconvolution, Journal of Computational and Applied Mathematics, 2018, 336: 425–438.

[12] Xiao-Guang Lv, Fang Li and Tieyong Zeng, Convex blind image deconvolution with inverse filtering, Inverse Problems, 2018, 34: 035003 (29pp).

[13] Xiao-Guang Lv, Fang Li, Binary image deblurring with automatic binary value estimation, Journal of Electronic Imaging, 2018, 27(3), 033043.

[14] Fang Li and Xiao-Guang Lv*, A Decoupled method for image inpainting with patch-based low rank regularization, Applied Mathematics and Computation, 2017, 314: 334–348.

[15] Jun Liu, Ting-Zhu Huang, Xiao-Guang Lv, Si Wang, High-order total variation-based Poissonian image deconvolution with spatially adapted regularization parameter, Applied Mathematical Modelling, 2017, 45: 516–529.

[16] Xiao-Guang Lv, Le Jiang, Jun Liu. Deblurring Poisson noisy images by total variation with overlapping group sparsity, Applied Mathematics and Computation, 2016, 289: 132-148.

[17] Jun Liu, Ting-Zhu Huang, Gang Liu, Si Wang, Xiao-Guang Lv, Total variation with overlapping group sparsity for speckle noise, Neurocomputing, 2016, 216: 502-513.

[18] Gang Liu, Ting-Zhu Huang, Xiao-Guang Lv and Jun Liu, New inexact explicit thresholding/shrinkage formulas for inverse problems with overlapping group sparsity, EURASIP Journal on Image and Video Processing, 2016, 2016:18, DOI 10.1186/s13640-016-0118-5.

[19] Xiao-Guang Lv, Yong-Zhong Song, Fang Li. An efficient nonconvex regularization for wavelet frame and total variation based image restoration, Journal of Computational and Applied Mathematics, 2015, 290: 553-566.

[20] Le Jiang, Jin Huang, Xiao-Guang Lv* and Jun Liu. Alternating direction method for the high-order total variation-based Poisson noise removal problem, Numerical algorithms, 2015, 69: 495-516.

[21] Xiao-Guang Lv, Ting-Zhu Huang, Le Jiang, Jun Liu. Two global iterative methods for ill-posed problems from image restoration, Journal of Computational Analysis and Applications, 2015, 18(2): 219-237.

[22] Jun Liu, Ting -Zhu Huang, Ivan W. Selesnick, Xiao-Guang Lv, Po -Yu Chen. Image restoration using total variation with overlapping group sparsity, Information Sciences, 2015, 295: 232-246.

[23] Gang Liu, Ting-Zhu Huang, Jun Liu, Xiao-Guang Lv. Total Variation with Overlapping Group Sparsity for Image Deblurring under Impulse Noise, PLOS ONE, 2015, 10( 4): e0122562.

[24] Jun Liu, Ting-Zhu Huang, Xiao-Guang Lv, Restoration of blurred color images with impulse noise, Computers and Mathematics with Applications, 2015, 70(6):1255-1265.

[25] Le Jiang, Jin Huang, Jun Liu, Xiao-Guang Lv*, A combined first-order and second-order variation approach for multiplicative noise removal, ANZIAM Journal, 2014, 56(2): 116-137.

[26] Le Jiang, Jin Huang, Xiao-Guang Lv* and Jun Liu, High-Order Total Variation-Based Image Restoration with Spatially Adapted Parameter Selection, Proceedings of International Conference on Computer Science and Information Technology, Advances in Intelligent Systems and Computing, 2014, 255: 67-74.

[27] Jun Liu, Ting-Zhu Huang, Xiao-Guang Lv, Hao Xu, and Xi-Le Zhao. Global Quasi-Minimal Residual Method for Image Restoration, Mathematical Problems in Engineering, 2014, Volume 2014, Article ID 943072.

[28] Cheng Guang-Hui, Rao Xi, Xiao-Guang Lv. The comparisons of two special Hermitian and skew-Hermitian splitting methods for image restoration, Applied Mathematical Modelling, 2014, 39(3-4):1275–1280.

[29] Jie Huang, Ting-Zhu Huang, Xi-Le Zhao, Xiao-Guang Lv. Two soft-thresholding based iterative algorithms for image deblurring, Information Sciences, 2014, 271: 179-195.

[30] Yi Xu, Ting-Zhu Huang, Jun Liu, Xiao-Guang Lv. An augmented Lagrangian algorithm for total bounded variation regularization based image deblurring, Journal of the Franklin Institute, 2014, 351: 3053–3067.

[31] Hao Xu, Ting-Zhu Huang, Xiao-Guang Lv, Jun Liu. The Implementation of LSMR in Image Deblurring, Applied Mathematics & Information Sciences, 2014, 8(6):3041-3048.

[32] Si Wang, Ting-Zhu Huang, Jun Liu, Xiao-Guang Lv. An alternating iterative algorithm for image deblurring and denoising problems, Communications in Nonlinear Science and Numerical Simulation, 2014, 19(3): 617-626.

授权发明专利

  1. 杨慧珍、吕小光,一种基于图像信息的快速扩展目标成像校正方法, 2017.09, 中国,201510575428。

    荣誉及获奖

    1.连云港市青年科技奖,2013。

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