Nanocrystalline SEM image restoration based on fractional-order TV and nuclear norm

Ruini Zhao; Ruini Zhao

doi:10.3934/era.2024228

Electronic Research Archive

2024, Volume 32, Issue 8: 4954-4968. doi: 10.3934/era.2024228

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Research article

Nanocrystalline SEM image restoration based on fractional-order TV and nuclear norm

Ruini Zhao ^,

College of ASEAN Studies, Guangxi Minzu University, Nanning 530006, China

Received: 28 April 2024 Revised: 05 August 2024 Accepted: 13 August 2024 Published: 16 August 2024

To obtain high-quality nanocrystalline scanning electron microscopy (SEM) images, this paper proposed a Poisson denoising model that combined the fractional-order total variation (TV) and nuclear norm regularizers. The developed novel model integrated the superiorities of fractional-order TV and nuclear norm constraints, which contributed to significantly improving the accuracy of image restoration while preventing the staircase effect and preserving edge details. By combining the variable separation method and singular value thresholding method, an improved alternating direction method of multipliers was developed for numerical computation. Compared with some existing popular solvers, numerical experiments demonstrated the superiority of the new method in visual effects and quality evaluation.
- image restoration,
- Poisson noise,
- fractional-order TV,
- nuclear norm,
- alternating direction method of multipliers
Citation: Ruini Zhao. Nanocrystalline SEM image restoration based on fractional-order TV and nuclear norm[J]. Electronic Research Archive, 2024, 32(8): 4954-4968. doi: 10.3934/era.2024228

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Abstract

To obtain high-quality nanocrystalline scanning electron microscopy (SEM) images, this paper proposed a Poisson denoising model that combined the fractional-order total variation (TV) and nuclear norm regularizers. The developed novel model integrated the superiorities of fractional-order TV and nuclear norm constraints, which contributed to significantly improving the accuracy of image restoration while preventing the staircase effect and preserving edge details. By combining the variable separation method and singular value thresholding method, an improved alternating direction method of multipliers was developed for numerical computation. Compared with some existing popular solvers, numerical experiments demonstrated the superiority of the new method in visual effects and quality evaluation.

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