报告题目:Image restoration via the local adaptive TV-based regularization
报 告人:河南大学庞志峰
时 间:2021年5月28日16:00-17:00
地 点:8号楼425
报告摘要:Image denoising problem still remains an active research field in the image processing. In the proposed model, how to describe the local structure of image is very important to improve the denoising quality. This paper proposes an image denoising model based on the adaptive weighted TVp regularization, where the regularization term can efficiently depict local structures by coupling the rotation matrix and the weighted matrix into the TVp-quasinorm. The adaptive angle used in the rotation matrix via the orientation field estimation mainly depends on the average phase angle of pixels within a suitable window, so this approach is more reasonable to express the local structure information. In addition, since the proposed model is nonsmooth and non-Lipschitz, we employ the alternating direction method of multipliers (ADMM) to solve it based on the half-quadratic scheme for solving the related ℓ2 − ℓp subproblem. We prove the convergence of the half-quadratic scheme under the framework of the alternating direction method (ADM) with a gradually decreasing smooth parameter. Furthermore, we also discuss the convergence of the ADMM. Some numerical comparisons with the classic TV-based models illustrate the good performance of our proposed model for the image denoising problem.
报告人简介:庞志峰, 博士, 河南大学数学与统计学院副教授, 硕士生导师。 南洋理工大学和香港城市大学博士后, 英国利物浦大学访问学者, 目前任河南省数字图形图像学会秘书长, 同时任中国生物医学工程学会医学人工智能专委会青年委员会委员, 中国工业与应用数学学会数学与医学交叉委员会委员和中国体视学学会智能成像分会委员。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和省部级项目各1项, 参与国家自然科学基金4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35篇(其中SCI收录28篇), 授权专利1项。自2010年到国内外多地访问, 2010.06-2011.03, 南洋理工大学数学物理学院, 博士后; 2011.12-2012.12, 香港城市大学电脑科学系, 博士后; 2014.02月-2014.08, 中国科学院数学与系统科学研究生院, 访问学者; 2015.07-2015.08, 南开大学陈省身数学研究所, 访问学者; 2016.01-2016.02, 香港中文大学系统工程与工程管理系, 访问学者;2016.08-2017.08, 利物浦大学(英国), 数学科学学院, 访问学者; 2018.01-2018.02, 香港理工大学访问学者, 2020.01-2020.02, 中科院深圳先进技术研究院访问学者。