Ramp preserving Perona–Malik model

Abstract

The Perona–Malik (PM) model, a classical anisotropic diffusion, can preserve edges while removing the noise. However, the defect of traditional PM model is tending to contain the staircase effect in the processed image. For this reason, a novel ramp preserving Perona–Malik (RPPM) model based on a new edge indicator is presented. In the RPPM model, the diffusion coefficient of the PM model is adaptively determined to introduce following property: isotropic diffusion in flat and ramp regions to prevent the staircase effect and anisotropic diffusion in edge regions to preserve edges. Comparative results on synthetic and real image denoising demonstrate that our model can preserve important structures, such as edges and ramps, while avoiding the speckles and the complex numerical implementation arising from high-order partial differential equations (PDEs).