Alternating Minimization Method for Total Variation Based Wavelet Shrinkage Model

被引:29
作者
Zeng, Tieyong [1 ]
Li, Xiaolong [2 ]
Ng, Michael [1 ]
机构
[1] Hong Kong Baptist Univ, Dept Math, Kowloon Tong, Hong Kong, Peoples R China
[2] Peking Univ, Inst Comp Sci & Technol, Beijing 100871, Peoples R China
关键词
Alternating minimization; convergence; Gibbs oscillation; wavelet shrinkage; total variation; IMAGE DECOMPOSITION; ALGORITHM; RECOVERY;
D O I
10.4208/cicp.210709.180310a
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this paper, we introduce a novel hybrid variational model which generalizes the classical total variation method and the wavelet shrinkage method. An alternating minimization direction algorithm is then employed. We also prove that it converges strongly to the minimizer of the proposed hybrid model. Finally, some numerical examples illustrate clearly that the new model outperforms the standard total variation method and wavelet shrinkage method as it recovers better image details and avoids the Gibbs oscillations.
引用
收藏
页码:976 / 994
页数:19
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