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

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.