Anisotropy

Algorithm

Service (business)

Effective diffusion coefficient

Applied mathematics

Edge-preserving smoothing

Convergence (economics)

Economics

Computer science

Mathematical optimization

Radiology

Thermodynamics

Physics

Diffusion

Anisotropic diffusion

Mathematics

Optics

Image (mathematics)

Enhanced Data Rates for GSM Evolution

Image denoising

Work (physics)

Mathematical analysis

Artificial intelligence

Geometry

Medicine

Economy

Economic growth

Diffusion equation

Partial differential equation

Noise reduction

Noise (video)

Magnetic resonance imaging

Computer vision

Computers & Mathematics with Applications

Anisotropic diffusion filtering is a widely used partial differential equation (PDE) based technique, which works effectively for removal of noise and preserving edges. This technique is highly dependent on diffusion coefficient and threshold parameter. In this work, we propose a new diffusion coefficient and image dependent threshold parameter which has a faster rate of convergence than those found in literature. The new technique outperforms the traditional models of anisotropic diffusion. Experimental results show the superiority of the proposed work over traditional anisotropic diffusion models.

An efficient anisotropic diffusion model for image denoising with edge preservation