Two New Efficient Iterative Regularization Methods for Image Restoration Problems
Iterative regularization methods are efficient regularization tools for image restoration problems. The IDR(s) and LSMR methods are state-of-the-arts iterative methods for solving large linear systems. Recently, they have attracted considerable attention. Little is known of them as iterative regular...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/129652 |
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| author | Chao Zhao Ting-Zhu Huang Xi-Le Zhao Liang-Jian Deng |
| author_facet | Chao Zhao Ting-Zhu Huang Xi-Le Zhao Liang-Jian Deng |
| author_sort | Chao Zhao |
| collection | DOAJ |
| description | Iterative regularization methods are efficient regularization tools for image restoration problems. The IDR(s) and LSMR methods are state-of-the-arts iterative methods for solving large linear systems. Recently, they have attracted considerable attention. Little is known of them as iterative regularization methods for image restoration. In this paper, we study the regularization properties of the IDR(s) and LSMR methods for image restoration problems. Comparative numerical experiments show that IDR(s) can give a satisfactory solution with much less computational cost in some situations than the classic method LSQR when the discrepancy principle is used as a stopping criterion. Compared to LSQR, LSMR usually produces a more accurate solution by using the L-curve method to choose the regularization parameter. |
| format | Article |
| id | doaj-art-9d36ea243a744c5e84428acf6e108a47 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-9d36ea243a744c5e84428acf6e108a472025-02-03T01:22:11ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/129652129652Two New Efficient Iterative Regularization Methods for Image Restoration ProblemsChao Zhao0Ting-Zhu Huang1Xi-Le Zhao2Liang-Jian Deng3School of Mathematical Sciences/Institute of Computational Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Mathematical Sciences/Institute of Computational Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Mathematical Sciences/Institute of Computational Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Mathematical Sciences/Institute of Computational Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaIterative regularization methods are efficient regularization tools for image restoration problems. The IDR(s) and LSMR methods are state-of-the-arts iterative methods for solving large linear systems. Recently, they have attracted considerable attention. Little is known of them as iterative regularization methods for image restoration. In this paper, we study the regularization properties of the IDR(s) and LSMR methods for image restoration problems. Comparative numerical experiments show that IDR(s) can give a satisfactory solution with much less computational cost in some situations than the classic method LSQR when the discrepancy principle is used as a stopping criterion. Compared to LSQR, LSMR usually produces a more accurate solution by using the L-curve method to choose the regularization parameter.http://dx.doi.org/10.1155/2013/129652 |
| spellingShingle | Chao Zhao Ting-Zhu Huang Xi-Le Zhao Liang-Jian Deng Two New Efficient Iterative Regularization Methods for Image Restoration Problems Abstract and Applied Analysis |
| title | Two New Efficient Iterative Regularization Methods for Image Restoration Problems |
| title_full | Two New Efficient Iterative Regularization Methods for Image Restoration Problems |
| title_fullStr | Two New Efficient Iterative Regularization Methods for Image Restoration Problems |
| title_full_unstemmed | Two New Efficient Iterative Regularization Methods for Image Restoration Problems |
| title_short | Two New Efficient Iterative Regularization Methods for Image Restoration Problems |
| title_sort | two new efficient iterative regularization methods for image restoration problems |
| url | http://dx.doi.org/10.1155/2013/129652 |
| work_keys_str_mv | AT chaozhao twonewefficientiterativeregularizationmethodsforimagerestorationproblems AT tingzhuhuang twonewefficientiterativeregularizationmethodsforimagerestorationproblems AT xilezhao twonewefficientiterativeregularizationmethodsforimagerestorationproblems AT liangjiandeng twonewefficientiterativeregularizationmethodsforimagerestorationproblems |