Directional 3D Peer-Group Filter for Color Image with Random Impulse Noise

Abstract

Peer-group filtering is the most basic approach to image denoising in the spatial domain; however, the effectiveness of this method degrades rapidly with an increase in the amount of noise. In this paper, we propose a novel 3D (3 dimensions) directional peer-group filter (referred to as 3DPGF) for the restoration of color images through the removal of random impulse noise. As with other switching methods, 3DPGF proceeds through two steps. Noise detection stage is first performed using a directional peer-group method, whereupon a 3D peer-group weighted-mean technique is used to remove the noise. Simulation results demonstrate that 3DPGF is able to enhance the accuracy in the identification and removal of noise.