PDE based Diffusion Filters for Image Denoising

• Published in: 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) pp. 1 - 6
• Main Authors: Yamini, R, Jeyalakshmi, R Ratha, Sowmini, R
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08.02.2023
• Subjects: edge enhancing and filter; Image edge detection; Linear diffusion; Maximum likelihood detection; Neural networks; Noise reduction; Nonlinear filters; Partial differential equations; Perona malik model; Tomography
• DOI: 10.1109/OTCON56053.2023.10114016

The main purpose of reducing noise is to enhance the quality of an image and to provide efficient information that are too minute. So, the main focus is on methods utilizing partial differential equations for removing the noise from the image. This paper focuses on utilizing diffusion equations, both isotropic and anisotropic diffusion, to reduce the noise level of the image. Specifically, we study the effectiveness of linear and nonlinear diffusion filters. Here we mainly discuss about following three models: Linear diffusion model and its limitations; Perona Malik model and its limitations; Edge Enhancing diffusion model (EED) and its limitations.