张军

2005.02-2010.01，南京理工大学模式识别与智能系统专业，博士;
1999.06-2002.07，武汉大学计算数学专业，硕士;
1995.09-1999.07: 武汉大学计算数学及其应用软件专业，学士

江苏省数学会计算数学分会理事，

江苏省运筹学会理事，

[1] 张军，肖亮，韦志辉. 图像复原的变分正则化建模——从整数阶到分数阶，国防工业出版社，2021年8月

[2] 肖亮、张军、韦志辉、刘鹏飞，“稀疏图像与信号处理：小波, 曲波，形态多样性”（译著），国防工业出版社，2015.

[3] 朱元国、饶玲、严涛、张军、李宝成等，矩阵分析与计算，国防工业出版社，2010.

[4] 许春根、张正军、张军. 计算机应用开发技术 (普通高等教育“十一五”国家级规划教材), 科学出版社, 2010.

[1] 张军，杨明博, 彭鹏，吴贞宇，郭超，基于随机样本分类增扩的GPR图像超分辨率重建方法，发明专利，202011384484.6，已受理

[2] 张军,查闰宝, . 一种基于图像补的低光子泊松图像复原方法，发明专利，ZL2020103603129，中国国家知识产权局，2022年10月14日

[3] 张军，刘海姣，韦志辉，李敏. 全变差正则化变分随机共振自适应暗图像滤波增强方法，发明专利，ZL201710467408.3, 中国国家知识产权局，2020年11月13日授权

[4] 张军,肖亮,韦志辉. 基于图像形态模糊隶属度的分数阶自适应相干斑滤波方法 2013.04.28~2033.04.27 (201210145403.6)

[5] 张军,肖亮,韦志辉. 基于分数阶差分加权的图像多步残差反馈迭代滤波方法 2012.05.10~2032.05.09 (201310157990.5)

[1].国家自然科学基金(面上基金), 基于数据驱动随机扩增和张量分析的低光子数Poisson图像重建, 61671243, 60万, 2017.01-2020.12, 主持

[2].国家自然科学基金(青年基金)，结构保持图像复原的分数阶正则化理论与算法，61101198，25万，2012.01—2014.12．主持

[3].江苏省自然科学基金（面上基金），基于分数阶稀疏性及几何正则化的MR图像压缩感知重建, BK2012800, 10万, 2012.07—2015.06. 主持

[4].中国博士后科学基金（二等），基于分数阶正则化的MR图像结构保持压缩感知重建，2012M511281，5万，2012.07—2014.07. 主持

[5].江苏省博士后基金，基于多形态分量分数阶稀疏性正则化的压缩感知图像重建方法，1102064C，1万，2012.01—2013.12. 主持

[6].国家自然科学基金面上项目，61471199，联合空谱上下文的高光谱遥感图像低秩表示分类理论与算法，2015/01-2018/12，83万，在研，参加（本人排名第二）

[7].基于形态成分结构化联合稀疏性的压缩感知照相机网络重建理论与算法, 国家自然科学基金 (No.61071146, 2011.01~2013.12). 参与

[8].基于形态分量分析的图像超分辨率重建机理与算法研究,国家自然科学基金(No.60672074, 2009.01~2011.12) . 参与

[9].基于分数阶变分偏微分方程的SAR图像复原理论与算法研究, 高等学校博士学科点基金 (No.200802880018, 2009.01~2011.12) . 参与

第一作者及通讯作者论文：

 [1] Jun Zhang, Linyan Zhao and Zhihui Wei. Poisson-Skellam distribution based regularization conditional random field method for photon-limited Poisson image denoising. Signal Processing, 2021,188: 108165（SCI）

[2] Runbao Zha, Jun Zhang(通讯作者) and Zhihui Wei. Multi-Components Low Dimensional Manifold Model for Photon limited Poisson Noisy Image Reconstruction. 2019 IEEE International Conference on Image Processing (ICIP), 2019: 1134-1137

[3] Ruifeng Hu and Jun Zhang(通讯作者). Accelerate Randomized Low Dimensional Manifold Method for Image Reconstruction. 2020 IEEE International Conference on Progress in Informatics and Computing, 2020:124-128

[4] Jiajun Fu and Jun Zhang(通讯作者). Fast Grouped High-order SVD Method for Poisson Noise Removal in Video Sequential Images. 2020 IEEE International Conference on Progress in Informatics and Computing, 2020:119-123

[5] Zhang Jun, Liu Haijiao and Wei Zhihui. Regularized variational dynamic stochastic resonance method for enhancement of dark and low-contrast image. Computers and Mathematics with Applications, 2018, 76(4): 774-787. (15 August 2018)（SCI）

[6] Wu Huapeng, Zhang Jun (通讯作者) and Wei Zhihui. High Resolution Similarity Directed Adjusted Anchored Neighborhood Regression for Single Image Super-Resolution.  IEEE Access 6 (2018): 25240-25247.

[7] Zhao Lingyan, Zhang Jun(通讯作者) and Wei Zhihui. Skellam Distribution Based Adaptive Two-stage Non-local Methods for Photon-limited Poisson Noisy Image Reconstruction，2017 IEEE International Conference on Image Processing (ISBN: 978-1-5090-2175-8), 2017.09

[8] Liu Haijiao, Jun Zhang(通讯作者) . Filtering Combined Dynamic Stochastic Resonance for Enhancement of Dark and Low-contrast Images. Proceedings of 2017 IEEE International Conference on Progress in Informatics and Computing (ISBN: 978-1-5386-1978-0), 2017.12

[9] Zhang Jun, Wei Zhihui and Xiao Liang. Bi-component decomposition based hybrid regularization method for partly-textured CS-MR image reconstruction. Signal Processing, 2016, 128: 274–290.(SCI: 000379706500027)

[10] Zhang Zhengrong, Zhang Jun(张军通讯作者), Wei Zhihui. Cartoon-texture composite regularization based non-blind deblurring method for partly-textured blurred images with Poisson noise. Signal Processing, 2015, 116: 127-140.(SCI: 000356980400013)

[11] Huang Nan, Zhang Jun(通讯作者). Exponential principal component analysis and non- local means based two-stage method for photon-limited Image reconstruction, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing ( 978-1-4673-9088-0), 2015.11

[12] Zhang Jun(张军), Wei Zhihui and Liang Xiao. A fast adaptive reweighted residual-feedback iterative algorithm for fractional-order total variation regularized multiplicative noise removal of partly-textured images. Signal Processing, 2014, 98: 381–395 (SCI:000331595000035)

[13] Zhang Jun, Wei Zhihui and Liang Xiao. Fractional-order Iterative Regularization Method for Total Variation Based Image Denoising. Journal of Electronic Imaging, 2012, 21(4): 043005-1 - 043005-1. (SCI: 000314506800007 )

[14] Zhang Jun, Wei Zhihui and Liang Xiao. Adaptive Fractional-order Multi-scale Method for Image Denoising. Journal of Mathematical Imaging and Vision，2012，43(1): 39–49 (SCI: 000302346000004)

[15] Zhang Jun(张军), Wei Zhihui and Xiao Liang. A Relaxed Split Bregman Iteration for Total Variation Regularized Image Denoising. 8^th Inernational Conference on Intelligent Computing Theories and Applications, 2011. Lecture Notes in Artificial Intelligence, 2012,7390: 189- 192 (EI: 20123415354302)

[16] Zhang Jun(张军), Wei Zhihui. A Class of Fractional-order Multi-scale Variational Models and Alternating Projection Algorithm for Image Denoising. Applied Mathematical Modelling, 2011, 35(5): 2516-2528. (SCI: 000287615300039)

[17] 张军，韦志辉. SAR图像去噪的分数阶多尺度变分PDE模型及自适应算法.电子与信息学报, 2010, 32(7): 1654-1659. (EI: 20103213128796)

[18] Zhang Jun(张军), Wei Zhihui. A Class of Multi-scale Models for Image Denoising in Negative Hilbert-Sobolev Spaces. Lecture Notes in Control and Information Science, Springer, 2006, 345: 584-592. (SCI: 000240385300061)

其他合作论文

[1] Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei. Pyramidal Dense Attention Networks for Single Image Super-resolution.IET Image Processing, 2022:1-11(SCI)

[2] Xiangxiang Qiu, Jun Zhang and Zhihui Wei. Exponential Family Graph Signal Recovery under Structural Constraint. 2020 IEEE International Conference on Progress in Informatics and Computing, 2020:129-134

[3] Hanyang Li, Hongyi Liu, Jun Zhang, Zebin Wu and Zhihui Wei. Non-Convex Relaxation Low-Rank Tensor Completion for Hyper-spectral Image Recovery, 2019 IEEE International Geoscience and Remote Sensing Symposium, 1935-1938

[4] Xiaofei Zhao, Hongyi Liu, Jun Zhang, et al. A Spectral Mapping Based Intensity Modulation for Pan-Sharpening. 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019: 843-846

[5] Li  Min, et al. Prediction of Lung Motion From Four-Dimensional Computer Tomography (4DCT) Images Using Bayesian Registration and Trajectory Modelling.  IEEE Access 6 (2018): 2803-2811.

[6] Liu Pengfei, Xiao Liang, Zhang Jun and Bushra Naz. Spatial-hessian-feature guided variational model for pan-sharpening. IEEE Transactions on Geoscience and Remote Sensing, 2016, (SCI:000373004000028)

[7] Liu Pengfei, Xiao Liang and Zhang Jun. A fast higher degree total variation minimization method for image restoration. International Journal of Computer Mathematics, 2015: 1-43. (SCI:000377224200010)

[8] Liu Pengfei, Xiao Liang and Zhang Jun(张军). Fast Second Degree Total Variation Method for Image Compressive Sensing. PloS one, 2015, 10(9): e0137115. (SCI：000361043100023)

[9] Fu Xujia, Huang Nan, Zhang Jun(张军). Improved algorithm for image TV regularization restoration model based on texture and contrast compensation, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing ( 978-1-4673-9088-0), 2015.11

[10] Tang Songze, Xiao Liang, Liu Pengfeiu, Zhang Jun, and Huang Lili. Edge and color preserving single image superresolution. Journal of Electronic Imaging, 2014, 23(3): 033002(12pages) (SCI: 000338984500003)

[11] Chen Huasong, Yan Keding，Zhang Jun and Li Zhenhua. Simultaneous cartoon-plus-texture image deconvolution by using variational image decomposition. SPIE/COS Photonics Asia. International Society for Optics and Photonics, 2014: 92732Q-92732Q-7. (EI: 20150700527291)

[12] Zhan, Tianming, Zhang Jun,, Xiao Liang and Wei Zhihui. An improved variational level set method for MR image segmentation and bias field correction. Magnetic resonance imaging,2013, 31(3): 439-47 (SCI:000316827400015)

[13] Wang Liqian, Xiao Liang, Zhang Jun, and Wei Zhihui. New image restoration method associated with tetrolets shrinkage and weighted anisotropic total variation. Signal processing, 2013, 93(4): 661-670 (SCI: 000315316400005)

[14] 詹天明, 肖亮, 张军, 韦志辉. 基于时空连续约束的 4D 脑图像分割模型. 电子学报, 2013, 41(8): 1592-1597.(EI: 20134917057661)

[19] Ge Qi, Xiao Liang, Zhang Jun, and Wei Zhihui. An improved region-based model with local statistical features for image segmentation, Pattern Recognition, 2012,45: 1578-1590 .(SCI: 000300459000029)

[20] Ge Qi, Xiao Liang, Zhang Jun, and Wei Zhihui. A Robust Patch-Statistical Active Contour Model for Image Segmentation, Pattern Recognition letter, 2012, 33: 1549-1557 (SCI: 000307134100007)

[21] Ge Qi, Xiao Liang, Wei Zhihui and Zhang Jun(张军). An improved region-based model with local statistical feature. IEEE international conference on Image Processing, 2011, 3341-3344. (EI: 20120514730444)

[22] 詹天明,张军,韦志辉,肖亮,孙玉宝. 基于参数化互信息的脑MR图像分割与偏移场矫正模型及快速算法. 电子学报, 2011 39(12) : 2807-2812. (EI: 20120514736343)

[23] 詹天明,韦志辉,张建伟,肖亮,张军. 脑MR图像分割和偏移场矫正的耦合水平集模型.中国图象图形学报, 2011,16(11):2017-2023