Edge-preserving image restoration based on a weighted anisotropic diffusion model

Partial differential equation-based methods have been widely applied in image restoration. The anisotropic diffusion model has a good noise removal capability without affecting significant edges. However, existing anisotropic diffusion-based models closely depend on the diffusion coefficient function and threshold parameter. This paper proposes a new weighted anisotropic diffusion coefficient model with multiple scales, and it has a higher speed of closing to X-axis and exploits adaptive threshold parameters. Meanwhile, the proposed algorithm is verified to be suitable for multiple types of noise. Numerical metrics and visual comparison of simulation experiments show the proposed model has significant superiority in edge-preserving and staircase artifacts reducing over the existing anisotropic diffusion-based techniques.