腾讯会议：7568896432
邀请人：蔡邢菊教授
报告摘要：Jittering is a common phenomenon arising from the area of multimedia data compression and wireless video transmission. The visual abnormality of a jittered image is the jag in edge and loss of synchronization in latitudinal direction. Typically, the problem of intrinsic image dejittering is challenging to be tackled because of the ubiquitous noise in jittered data. In this paper, we develop a convex variational model for solving image dejittering problem by exerting high-order finite differences regularizer in objective function and exploiting linearization to constraints, which can be viewed as an amelioration of the bake-and-shake model (Kang and Shen, Image Vision Comput, 24:143--152, 2006). Upon the recent progress in convex optimization community, the proposed model can be efficiently solved by the first-order primal-dual algorithm. Numerical simulations on recovering both noiseless and noisy jittered data demonstrate the compelling performance of the proposed model.
报告人简介：
张文星，电子科技大学副教授，先后于山东师范大学（2006）、女王调教
（2009）、南京大学（2012）获得学士、硕士、博士学位。2014-2015年在法国图卢兹大学从事博士后研究。曾访问香港大学、香港中文大学、香港浸会大学等高校。主要研究兴趣为最优化理论与算法、变分不等式及应用。目前主持国家自然科学基金项目一项。在Math Comput, SIAM J Imaging Sci, Inverse Problems, J Sci Comput, IEEE-TMI, IEEE-TIP, IEEE-TASE等杂志发表论文20余篇。