A New Method For Removing High-Density Salt and Pepper Noise Based On Decision-based Based Algorithm

摘要

The thesis proposes an improved median filtering algorithm for the restoration of images that are highly corrupted by salt and pepper noise. The proposed algorithm (PA) replaces the noisy pixel with the median of the already processed pixel values by changing the processing structure and using iteration method to solve three specific situations when all the pixels in the selected window are corrupted by noise. It turns out that PA can efficiently remove the salt and pepper noise when the noise level is higher than 60%. Simulation results are given to illustrate that PA can be applied to gray scale image denoising and outperforms the existing methods.