On Semismooth Newton's Methods for Total Variation Minimization

Authors:
Michael K. Ng;Liqun Qi;Yu-Fei Yang;Yu-Mei Huang
Affiliations:
Centre for Mathematical Imaging and Vision and Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong;Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;College of Mathematics and Econometrics, Hunan University, Changsha, China;Centre for Mathematical Imaging and Vision and Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong and School of Information Science and Engineering, Lanzhou Universit ...
Venue:
Journal of Mathematical Imaging and Vision
Year:
2007

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Abstract

In [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton's methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms.