吴春林

  中国科学技术大学  博士   2001/09-2006/07；

  中国科学技术大学  学士   1997/09-2001/07；

    南开大学数学科学学院    副教授   2012/12 - ；

    新加坡国立大学        博士后   2010/07 - 2012/07；

    新加坡南洋理工大学     博士后   2008/03 - 2010/06；

    中国科学技术大学     博士后   2006/07 - 2008/03；

图像与几何计算，数值逼近与优化

本科课程：《最优化方法》，《计算几何》，《高等数学》，《高等数学》习题课；

研究生课程：《函数逼近论》；

1. 国家自然科学基金青年基金 1 项，  2014/01-2016/12, 已结题，主持;

2. 国家自然科学基金面上项目 1 项,   2019/01-2022/12,   在研,主持;

3. 国家自然科学基金重点项目 1 项,   2016/01-2020/12,  在研, 参加;

主要论文：

  

1. C. Zeng, R. Jia, C. Wu. An Iterative Support Shrinking Algorithm for Non-Lipschitz Optimization in Image Restoration. J. Mathematical Imaging and Vision, available online 2018.

  

2. W. Wang, S. Wen, C. Wu, J. Deng. Denoising Piecewise Constant Images with Selective Averaging and Outlier Removal. Numerical Mathematics: Theory, Methods and Applications, available online 2018. 

  

3. C. Zeng, C. Wu, On the discontinuity of images recovered by noncovex nonsmooth regularized isotropic models with box constraints. Adv. Comput. Math., available online 2018.

  

4. C. Zeng, C. Wu, On the edge recovery property of noncovex nonsmooth regularization in image restoration. SIAM J. Numer. Anal., 56:1168-1182, 2018.  

  

5. H. Zhang, C. Wu, J. Deng, Z. Liu, Y. Yang. A new two-stage mesh surface segmentation method. The Visual Computer,34: 1597-1615, 2018.

  

6. C. Wu, Z. Liu, S. Wen, A general truncated regularization framework for contrast-preserving variational signal and image restoration: motivation and implementation. SCI. CHINA Mathematics., 61:1711-1732, 2018.

  

7. X. Feng, C. Wu, C. Zeng, On the local and global minimizers of L0 gradient regularized model with box constraints for image restoration. Inverse Problems, 34, 095007, 2018.

  

8. W. Wang, C. Wu, J. Deng, A general selective averaging method for piecewise constant signal and image processing. J. Scientific Computing., 76:1078-1104, 2018.

  

9. S. Wali, Z. Liu, C. Wu, H. Chang. A boosting procedure for variational-based image restoration. Numerical Mathematics: Theory, Methods and Applications,11:49-73, 2018.

  

10. Z. Liu, H. Zhang, C. Wu, On geodesic curvature flow with level set formulation over triangulated surfaces, J. Scientific Computing., 70:631-661, 2017.

  

11. H. Chang,W. Huang, S.Huang, C. Guan, C. Wu, S. Sekar, K. K. Bhakoo, Y. Duan. A new variational method for bias correction and its applications to rodent brain extraction. IEEE Trans. Medical Imaging., 36: 721-733, 2017.

  

12. H. Zhang, C. Wu, J. Zhang, J. Deng. Variational mesh denoising using total variation and piecewise constant function space. IEEE Trans. Visualization and Computer Graphics.,21: 873-886, 2015.

  

13. Y. Duan, H. Chang, W. Huang, J. Zhou, Z. Lu, C. Wu. The L0 regularized Mumford–Shah model for bias correction and segmentation of medical images. IEEE Trans. Image Processing, 24: 3927-3938,2015.

  

14. C. Wu, On the continuity of images by transmission imaging. Communications in Mathematical Sciences., 11: 573-595, 2013.

  

15. J. Zhang, J. Zheng, C. Wu, J. Cai. Variational mesh decomposition. ACM Trans. Graphics, 31(3): article no. 21, 2012.

  

16. C. Wu, J. Zhang, Y. Duan, X.C. Tai. Augmented Lagrangian method for total variation based image restoration and segmentation over triangulated surfaces. J. Scientific Computing, 50: 145-166, 2012.

  

17. J. Hahn, C. Wu, X.C. Tai. Augmented Lagrangian method for generalized TV-Stokes model. J.Scientific Computing, 50: 235-264, 2012.

  

18. C. Wu, J. Zhang, X.C. Tai. Augmented Lagrangian method for total variation restoration with non-quadratic fidelity. Inverse Problems and Imaging., 5:237-261, 2011.

  

19. C. Wu,X.C. Tai. Augmented Lagrangian method, dual methods, and split Bregman iteration for ROF, vectorial TV, and high order models. SIAM J. Imaging Sciences., 3: 300-339, 2010.

  

20. C. Wu, X.C. Tai. A level set formulation of geodesic curvature flow on simplicial surfaces. IEEE Trans. Visualization and Computer Graphics, 16: 647–662, 2010.

  

21. C. Wu, J.Deng, F.Chen,X.C. Tai. Scale-space analysis of discrete filtering over arbitrary triangulated surfaces. SIAM J. Imaging Sciences., 2: 670-709, 2009.

  

22. H. Han, M. Yan, C. Wu. An energy regularization method for backward diffusion problem and its applications to image deblurring. Commun. Comput. Physics, 4: 177-194, 2008.

  

23. C. Wu, J. Deng, F. Chen. Fast data extrapolating. J. Comput. Appl. Math., 206: 146-157, 2007.