Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization

It has been proved that total generalized variation (TGV) can better preserve edges while suppressing staircase effect. In this paper, we propose an effective hybrid regularization model based on second-order TGV and wavelet frame. The proposed model inherits the advantages of TGV regularization and...

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Main Authors: Jianguang Zhu, Kai Li, Binbin Hao
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/3650128
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author Jianguang Zhu
Kai Li
Binbin Hao
author_facet Jianguang Zhu
Kai Li
Binbin Hao
author_sort Jianguang Zhu
collection DOAJ
description It has been proved that total generalized variation (TGV) can better preserve edges while suppressing staircase effect. In this paper, we propose an effective hybrid regularization model based on second-order TGV and wavelet frame. The proposed model inherits the advantages of TGV regularization and wavelet frame regularization, can eliminate staircase effect while protecting the sharp edge, and simultaneously has good capability of sparsely estimating the piecewise smooth functions. The alternative direction method of multiplier (ADMM) is employed to solve the new model. Numerical results show that our proposed model can preserve more details and get higher image visual quality than some current state-of-the-art methods.
format Article
id doaj-art-7114fdd6ac0c4a5dace9682b86e126f1
institution OA Journals
issn 1076-2787
1099-0526
language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-7114fdd6ac0c4a5dace9682b86e126f12025-08-20T02:06:35ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/36501283650128Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame RegularizationJianguang Zhu0Kai Li1Binbin Hao2College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Science, China University of Petroleum, Qingdao 266580, ChinaIt has been proved that total generalized variation (TGV) can better preserve edges while suppressing staircase effect. In this paper, we propose an effective hybrid regularization model based on second-order TGV and wavelet frame. The proposed model inherits the advantages of TGV regularization and wavelet frame regularization, can eliminate staircase effect while protecting the sharp edge, and simultaneously has good capability of sparsely estimating the piecewise smooth functions. The alternative direction method of multiplier (ADMM) is employed to solve the new model. Numerical results show that our proposed model can preserve more details and get higher image visual quality than some current state-of-the-art methods.http://dx.doi.org/10.1155/2019/3650128
spellingShingle Jianguang Zhu
Kai Li
Binbin Hao
Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
Complexity
title Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
title_full Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
title_fullStr Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
title_full_unstemmed Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
title_short Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization
title_sort image restoration by second order total generalized variation and wavelet frame regularization
url http://dx.doi.org/10.1155/2019/3650128
work_keys_str_mv AT jianguangzhu imagerestorationbysecondordertotalgeneralizedvariationandwaveletframeregularization
AT kaili imagerestorationbysecondordertotalgeneralizedvariationandwaveletframeregularization
AT binbinhao imagerestorationbysecondordertotalgeneralizedvariationandwaveletframeregularization