A Weberized Total Variance Regularization-based Image Multiplicative Noise Model
This paper considers Weber's law and proposes a new non-convex model for images contaminated by Gaussian noise and Rayleigh noise. The alternating direction method of multipliers (abbreviated as ADMM) is a recent popular method that can handle convex and non-convex problems well. This paper com...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Slovenian Society for Stereology and Quantitative Image Analysis
2023-07-01
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| Series: | Image Analysis and Stereology |
| Subjects: | |
| Online Access: | https://www.ias-iss.org/ojs/IAS/article/view/2837 |
| _version_ | 1797783797671919616 |
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| author | Xinyao Yu Donghong Zhao |
| author_facet | Xinyao Yu Donghong Zhao |
| author_sort | Xinyao Yu |
| collection | DOAJ |
| description | This paper considers Weber's law and proposes a new non-convex model for images contaminated by Gaussian noise and Rayleigh noise. The alternating direction method of multipliers (abbreviated as ADMM) is a recent popular method that can handle convex and non-convex problems well. This paper compares denoising effect between ADMM and the Euler-Lagrange equation method applied to the non-convex model. The numerical experimental results show that ADMM performs better and has a higher Peak Signal to Noise Ratio. |
| first_indexed | 2024-03-13T00:30:58Z |
| format | Article |
| id | doaj.art-6de31c93f81149cb974e75e4a6467574 |
| institution | Directory Open Access Journal |
| issn | 1580-3139 1854-5165 |
| language | English |
| last_indexed | 2024-03-13T00:30:58Z |
| publishDate | 2023-07-01 |
| publisher | Slovenian Society for Stereology and Quantitative Image Analysis |
| record_format | Article |
| series | Image Analysis and Stereology |
| spelling | doaj.art-6de31c93f81149cb974e75e4a64675742023-07-10T14:42:40ZengSlovenian Society for Stereology and Quantitative Image AnalysisImage Analysis and Stereology1580-31391854-51652023-07-01422657610.5566/ias.28371096A Weberized Total Variance Regularization-based Image Multiplicative Noise ModelXinyao Yu0Donghong Zhao1University of Science and Technology BeijingUniversity of Science and Technology BeijingThis paper considers Weber's law and proposes a new non-convex model for images contaminated by Gaussian noise and Rayleigh noise. The alternating direction method of multipliers (abbreviated as ADMM) is a recent popular method that can handle convex and non-convex problems well. This paper compares denoising effect between ADMM and the Euler-Lagrange equation method applied to the non-convex model. The numerical experimental results show that ADMM performs better and has a higher Peak Signal to Noise Ratio.https://www.ias-iss.org/ojs/IAS/article/view/2837admmeuler-lagrange equationimage denoisingmultiplicative noisepartial differential equationweberized total variation |
| spellingShingle | Xinyao Yu Donghong Zhao A Weberized Total Variance Regularization-based Image Multiplicative Noise Model Image Analysis and Stereology admm euler-lagrange equation image denoising multiplicative noise partial differential equation weberized total variation |
| title | A Weberized Total Variance Regularization-based Image Multiplicative Noise Model |
| title_full | A Weberized Total Variance Regularization-based Image Multiplicative Noise Model |
| title_fullStr | A Weberized Total Variance Regularization-based Image Multiplicative Noise Model |
| title_full_unstemmed | A Weberized Total Variance Regularization-based Image Multiplicative Noise Model |
| title_short | A Weberized Total Variance Regularization-based Image Multiplicative Noise Model |
| title_sort | weberized total variance regularization based image multiplicative noise model |
| topic | admm euler-lagrange equation image denoising multiplicative noise partial differential equation weberized total variation |
| url | https://www.ias-iss.org/ojs/IAS/article/view/2837 |
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