数学与统计学院学术报告[2020] 006 号

(高水平大学建设系列报告359号)

报告题目: Image restoration and decomposition via the adaptive direction total variation regularization

报告人： 庞志峰 教授 （河南大学）

报告时间：2020年1月14日下午2:30—3:30

报告地点： 汇星楼501室

报告内容：Image restoration problem still remains an active research field in the image processing. To improve the denoising quality, it is very important to describe the local structure of the image in the proposed model. This fact motivates us to introduce an adaptive weighted TV p regularization-based denoising model, where the rotation matrix and the weighted matrix depend on the local structure of the image. Specially, these two matrices can enhance the diffusion of the responding Euler-Lagrangian equation along with the tangential direction of the edge. This procedure offers more control over the regularization and then allows more denoising in smooth regions and less denoising when processing edge regions. In ad- dition, since the proposed model is nonsmooth and non-Lipschitz, we employ the alternating direction method of multipliers (ADMM) to solve it with the help of using the half-quadratic scheme to solve the related [1]l2−lp subproblem. As one application, we also extend our method to the image decomposition problem. Some numerical comparisons show that the proposed model leads to considerable performance gains when tested on several denoising tasks.

报告人简历：庞志峰，河南大学数学与统计学院副教授，硕士生导师。目前任河南省数字图形图像学会常务理事和副秘书长。新加坡南阳理工大学和香港城市大学博士后，英国利物浦大学，香港中文大学和香港理工大学访问学者。主要研究图像处理中的数学理论与数值算法。曾主持国家自然科学基金1项，参与国家自然科学基金3项，国家重点基础研究发展计划(973项目)1项。现发表相关学术论文27篇(其中SCI收录25篇), 授权专利1项。

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数学与统计学院

　　　　　　　　　　　　　　　　　　　　　　　　 2020年1月14日