On Nonconvex Regularized Models for Image and surface Restoration Problems
报告题目(Title)：On Nonconvex Regularized Models for Image and surface Restoration Problems
报告人(Speaker)：吴春林 教授 （南开大学数学科学学院）
地点(Place)：腾讯会议 ID：567 367 237
时间(Time)：2020年10月26日（星期一） 18:00-19:00
邀请人(Inviter)：刘 君
报告摘要
Variational methods with regularization techniques have become an important kind of methods image restoration. The convex total variation (TV) regularization, although achieved great successes,suffers from a contrast reduction effect. Recently nonconvex regularization techniques become popular. In this talk, I will mainly present three parts. The first one is a motivation of using nonconvex regularizations and a general truncated regularization framework. The second is a lower bound theory for nonconvex regularized models, which shows the good edge recovery property. The third one is an extension of total variation for surface denoising.
主讲人简介
吴春林，南开大学数学科学学院教授。吴博士于2006年在中国科学技术大学获得博士学位。曾在中国科学技术大学，新加坡南洋理工大学，新加坡国立大学从事博士后研究工作。2012年吴春林加入南开大学数学科学学院。他的研究兴趣包括图像与几何计算，数值逼近与优化。近年来吴博士在国际图像科学及计算数学知名杂志比如SIAM J. Imaging Sciences, SIAM J. Numerical Analysis， SIAM J. Scientific Computing, Applied Comput. Harmonic Analysis, Inverse Problems, J. Sci. Comput., Inverse Prob. Imaging, ACM TOG, IEEE TVCG,IEEE TIP, IEEE TMI等上发表多篇学术论文。
