M107, Hong-Jing Hall, NCU
(中央大學鴻經館 M107)
Augmented Lagrangian method for Rudin-Osher-Fatemi image model
Pei-Chiang Shao (National Central University)
Abstract
In this talk we will introduce the augmented Lagrangian method (ALM) [1, 2] for solving the Rudin-Osher-Fatemi total variation model [3]. The relation between ALM and split Bregman iteration will also be discussed.
References
[1] X. C. Tai and C. Wu, Augmented Lagrangian method, dual methods and split Bregman iteration for ROF model, in Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision, 2009, Springer.
[2] C. Wu and X. C. Tai, Augmented Lagrangian method, dual methods and split Bregman iteration for ROF, vectorial TV, and high order models, SIAM Journal on Imaging Sciences, 1, (2008), pp. 248-272.
[3] L. I. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica D, 60 (1992), pp. 259-268.
