Poisson noise and Gaussian noise separation through copula theory
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/01/29
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Indian UGC (journal)
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Refrences41
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Abdelghani Ghazdali
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Aissam Hadri
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Amine Laghrib
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Mourad Nachaoui
Cite
Ghazdali, Abdelghani, et al. “Poisson Noise and Gaussian Noise Separation through Copula Theory”. Multimedia Tools and Applications, 2024, https://doi.org/10.1007/s11042-023-17898-y.
Ghazdali, A., Hadri, A., Laghrib, A., & Nachaoui, M. (2024). Poisson noise and Gaussian noise separation through copula theory. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-17898-y
Ghazdali, Abdelghani, Aissam Hadri, Amine Laghrib, and Mourad Nachaoui. “Poisson Noise and Gaussian Noise Separation through Copula Theory”. Multimedia Tools and Applications, 2024. https://doi.org/10.1007/s11042-023-17898-y.
1.
Ghazdali A, Hadri A, Laghrib A, Nachaoui M. Poisson noise and Gaussian noise separation through copula theory. Multimedia Tools and Applications. 2024;.
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Addressing image and Poisson noise deconvolution problem using deep learning approaches | Computational Intelligence |
| 2 | 2023 |
| A non-convex PDE-constrained denoising model for impulse and Gaussian noise mixture reduction | Inverse Problems and Imaging |
| 7 | 2023 |
| An improved bilevel optimization approach for image super-resolution based on a fractional diffusion tensor | Journal of the Franklin Institute |
| 6 | 2022 |
| A review on self-adaptation approaches and techniques in medical image denoising algorithms | Multimedia Tools and Applications |
| 5 | 2022 |
A non-convex non-smooth bi-level parameter learning for impulse and Gaussian noise mixture removing | Communications on Pure and Applied Analysis |
| 10 | 2022 |
Refrences Analysis
The category
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics 17
is the most frequently represented among the references in this article. It primarily includes studies from Signal Processing and IEEE Access. The chart below illustrates the number of referenced publications per year.