An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations
To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization. In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient informa...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2014/934834 |
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| _version_ | 1832545603758850048 |
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| author | Kui Liu Jieqing Tan Benyue Su |
| author_facet | Kui Liu Jieqing Tan Benyue Su |
| author_sort | Kui Liu |
| collection | DOAJ |
| description | To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization. In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient information of the image. When the pixels belong to the smooth regions, Tikhonov regularization is adopted, which can eliminate the staircase artifacts. When the pixels locate at the edges, total variation regularization is selected, which can preserve the edges. We employ the split Bregman method to solve our model. Experimental results demonstrate that our model can obtain better performance than those of other models. |
| format | Article |
| id | doaj-art-ca258f466cdd4e418216d3d600ffda99 |
| institution | Kabale University |
| issn | 1687-5680 1687-5699 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Multimedia |
| spelling | doaj-art-ca258f466cdd4e418216d3d600ffda992025-02-03T07:25:17ZengWileyAdvances in Multimedia1687-56801687-56992014-01-01201410.1155/2014/934834934834An Adaptive Image Denoising Model Based on Tikhonov and TV RegularizationsKui Liu0Jieqing Tan1Benyue Su2School of Computer and Information, Hefei University of Technology, Hefei 23009, ChinaSchool of Computer and Information, Hefei University of Technology, Hefei 23009, ChinaSchool of Computer and Information, Anqing Normal University, Anqing 246011, ChinaTo avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization. In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient information of the image. When the pixels belong to the smooth regions, Tikhonov regularization is adopted, which can eliminate the staircase artifacts. When the pixels locate at the edges, total variation regularization is selected, which can preserve the edges. We employ the split Bregman method to solve our model. Experimental results demonstrate that our model can obtain better performance than those of other models.http://dx.doi.org/10.1155/2014/934834 |
| spellingShingle | Kui Liu Jieqing Tan Benyue Su An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations Advances in Multimedia |
| title | An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations |
| title_full | An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations |
| title_fullStr | An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations |
| title_full_unstemmed | An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations |
| title_short | An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations |
| title_sort | adaptive image denoising model based on tikhonov and tv regularizations |
| url | http://dx.doi.org/10.1155/2014/934834 |
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