A New Variational Approach for Multiplicative Noise and Blur Removal.
This paper proposes a new variational model for joint multiplicative denoising and deblurring. It combines a total generalized variation filter (which has been proved to be able to reduce the blocky-effects by being aware of high-order smoothness) and shearlet transform (that effectively preserves a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5283674?pdf=render |
| _version_ | 1819364847068905472 |
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| author | Asmat Ullah Wen Chen Mushtaq Ahmad Khan HongGuang Sun |
| author_facet | Asmat Ullah Wen Chen Mushtaq Ahmad Khan HongGuang Sun |
| author_sort | Asmat Ullah |
| collection | DOAJ |
| description | This paper proposes a new variational model for joint multiplicative denoising and deblurring. It combines a total generalized variation filter (which has been proved to be able to reduce the blocky-effects by being aware of high-order smoothness) and shearlet transform (that effectively preserves anisotropic image features such as sharp edges, curves and so on). The new model takes the advantage of both regularizers since it is able to minimize the staircase effects while preserving sharp edges, textures and other fine image details. The existence and uniqueness of a solution to the proposed variational model is also discussed. The resulting energy functional is then solved by using alternating direction method of multipliers. Numerical experiments showing that the proposed model achieves satisfactory restoration results, both visually and quantitatively in handling the blur (motion, Gaussian, disk, and Moffat) and multiplicative noise (Gaussian, Gamma, or Rayleigh) reduction. A comparison with other recent methods in this field is provided as well. The proposed model can also be applied for restoring both single and multi-channel images contaminated with multiplicative noise, and permit cross-channel blurs when the underlying image has more than one channel. Numerical tests on color images are conducted to demonstrate the effectiveness of the proposed model. |
| first_indexed | 2024-12-24T23:05:26Z |
| format | Article |
| id | doaj.art-e4e37b9d516745379e35c07dc17c5991 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-24T23:05:26Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-e4e37b9d516745379e35c07dc17c59912022-12-21T16:35:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01121e016178710.1371/journal.pone.0161787A New Variational Approach for Multiplicative Noise and Blur Removal.Asmat UllahWen ChenMushtaq Ahmad KhanHongGuang SunThis paper proposes a new variational model for joint multiplicative denoising and deblurring. It combines a total generalized variation filter (which has been proved to be able to reduce the blocky-effects by being aware of high-order smoothness) and shearlet transform (that effectively preserves anisotropic image features such as sharp edges, curves and so on). The new model takes the advantage of both regularizers since it is able to minimize the staircase effects while preserving sharp edges, textures and other fine image details. The existence and uniqueness of a solution to the proposed variational model is also discussed. The resulting energy functional is then solved by using alternating direction method of multipliers. Numerical experiments showing that the proposed model achieves satisfactory restoration results, both visually and quantitatively in handling the blur (motion, Gaussian, disk, and Moffat) and multiplicative noise (Gaussian, Gamma, or Rayleigh) reduction. A comparison with other recent methods in this field is provided as well. The proposed model can also be applied for restoring both single and multi-channel images contaminated with multiplicative noise, and permit cross-channel blurs when the underlying image has more than one channel. Numerical tests on color images are conducted to demonstrate the effectiveness of the proposed model.http://europepmc.org/articles/PMC5283674?pdf=render |
| spellingShingle | Asmat Ullah Wen Chen Mushtaq Ahmad Khan HongGuang Sun A New Variational Approach for Multiplicative Noise and Blur Removal. PLoS ONE |
| title | A New Variational Approach for Multiplicative Noise and Blur Removal. |
| title_full | A New Variational Approach for Multiplicative Noise and Blur Removal. |
| title_fullStr | A New Variational Approach for Multiplicative Noise and Blur Removal. |
| title_full_unstemmed | A New Variational Approach for Multiplicative Noise and Blur Removal. |
| title_short | A New Variational Approach for Multiplicative Noise and Blur Removal. |
| title_sort | new variational approach for multiplicative noise and blur removal |
| url | http://europepmc.org/articles/PMC5283674?pdf=render |
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