High Order Total Variational Denoising Algorithm Based on lOverlapping Combination Sparse

作     者：Binxin Tang Xianchun Zhou Chengcheng Cui Yang Rui 

作者机构：School of Electronic and Information EngineeringNanjing University of Information Science and Technology School of Artificial IntelligenceNanjing University of Information Science and Technology 

出 版 物：《Instrumentation》 (仪器仪表学报(英文版))

年 卷 期：2024年

页      面：30-40页

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：funded by National Nature Science Foundation of China grant number 61302188 

摘      要：For addressing impulse noise in images,this paper proposes a denoising algorithm for non-convex impulse noise images based on the l0norm fidelity *** the total variation of the l0norm has a better denoising effect on the pulse noise,it is chosen as the model fidelity term,and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase *** the same time,the alternating direction method of multipliers,the majorizationminimization method and the mathematical program with equilibrium constraints were used to solve the *** results show that the proposed model can effectively suppress the staircase effect in smooth regions,protect the image edge details,and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.