A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise
The removal of mixed Gaussian-impulse noise plays an important role in many areas, such as remote sensing. However, traditional methods may be unaware of promoting the degree of the sparsity adaptively after decomposing into low rank component and sparse component. In this paper, a new problem formu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2017/2520301 |
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| author | Han Pan Zhongliang Jing Lingfeng Qiao Minzhe Li |
| author_facet | Han Pan Zhongliang Jing Lingfeng Qiao Minzhe Li |
| author_sort | Han Pan |
| collection | DOAJ |
| description | The removal of mixed Gaussian-impulse noise plays an important role in many areas, such as remote sensing. However, traditional methods may be unaware of promoting the degree of the sparsity adaptively after decomposing into low rank component and sparse component. In this paper, a new problem formulation with regular spectral k-support norm and regular k-support l1 norm is proposed. A unified framework is developed to capture the intrinsic sparsity structure of all two components. To address the resulting problem, an efficient minimization scheme within the framework of accelerated proximal gradient is proposed. This scheme is achieved by alternating regular k-shrinkage thresholding operator. Experimental comparison with the other state-of-the-art methods demonstrates the efficacy of the proposed method. |
| format | Article |
| id | doaj-art-15fd86e8b20e4e5d82cb75092bd4d1cf |
| institution | OA Journals |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-15fd86e8b20e4e5d82cb75092bd4d1cf2025-08-20T02:02:43ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322017-01-01201710.1155/2017/25203012520301A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse NoiseHan Pan0Zhongliang Jing1Lingfeng Qiao2Minzhe Li3School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, ChinaSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, ChinaSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, ChinaSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, ChinaThe removal of mixed Gaussian-impulse noise plays an important role in many areas, such as remote sensing. However, traditional methods may be unaware of promoting the degree of the sparsity adaptively after decomposing into low rank component and sparse component. In this paper, a new problem formulation with regular spectral k-support norm and regular k-support l1 norm is proposed. A unified framework is developed to capture the intrinsic sparsity structure of all two components. To address the resulting problem, an efficient minimization scheme within the framework of accelerated proximal gradient is proposed. This scheme is achieved by alternating regular k-shrinkage thresholding operator. Experimental comparison with the other state-of-the-art methods demonstrates the efficacy of the proposed method.http://dx.doi.org/10.1155/2017/2520301 |
| spellingShingle | Han Pan Zhongliang Jing Lingfeng Qiao Minzhe Li A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise Applied Computational Intelligence and Soft Computing |
| title | A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise |
| title_full | A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise |
| title_fullStr | A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise |
| title_full_unstemmed | A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise |
| title_short | A Regular k-Shrinkage Thresholding Operator for the Removal of Mixed Gaussian-Impulse Noise |
| title_sort | regular k shrinkage thresholding operator for the removal of mixed gaussian impulse noise |
| url | http://dx.doi.org/10.1155/2017/2520301 |
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