期刊
COMPUTERS & MATHEMATICS WITH APPLICATIONS
卷 77, 期 5, 页码 1255-1272出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.camwa.2018.11.003
关键词
Cauchy noise; Total variation and high-order total variation; Adaptive regularization parameters; Alternating direction method of multipliers; Image restoration
资金
- NSFC, China [61876203, 61772003]
- Fundamental Research Funds for the Central Universities, China [ZYGX2016J132]
- Science Strength Promotion Programme of UESTC, China
- National Postdoctoral Program for Innovative Talents [BX20180252]
- Fuyang Municipal Government-Fuyang Normal University Horizontal Cooperation, China Projects [XDHX201727]
In this paper, we propose a novel model to restore an image corrupted by blur and Cauchy noise. The model is composed of a data fidelity term and two regularization terms including total variation and high-order total variation. Total variation provides well-preserved edge features, but suffers from staircase effects in smooth regions, whereas high-order total variation can alleviate staircase effects. Moreover, we introduce a strategy for adaptively selecting regularization parameters. We develop an efficient alternating minimization algorithm for solving the proposed model. Numerical examples suggest that the proposed method has the advantages of better preserving edges and reducing staircase effects. (C) 2018 Elsevier Ltd. All rights reserved.
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