TY - JOUR
T1 - A Fourth Order Dual Method for Iteration Regularization with H-1 Fidelity Based Denoising
AU - 
JO - Journal of Information and Computing Science
VL - 3
SP - 172
EP - 178
PY - 2024
DA - 2024/01
SN - 2
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22795.html
KW - image denoising
KW -  total variation
KW -  fourth order dual method
KW -  iterative regularization

AB - In this paper, we propose iterative regularization for image denoising problems, based on the total 
variation minimizing models proposed by Rudin, Osher, and Fatemi(ROF). Besides, considering the staircase 
occuring in the process of denoising, we combine the higher order derivatives, and use iterative scheme. The 
fourth order dual method is used to solve the minimization  problems. The numerical experiments  show the 
iterative procedure preserves more details and reduces staircasing. Besides, it can be claimed that the fourth 
order dual method is more faster and stable than time marching algorithms.