Title :
A New Adaptive Weighted Mean Filter for Removing Salt-and-Pepper Noise
Author :
Peixuan Zhang ; Fang Li
Author_Institution :
Dept. of Math., East China Normal Univ. Shanghai, Shanghai, China
Abstract :
In this letter, we propose a new adaptive weighted mean filter (AWMF) for detecting and removing high level of salt-and-pepper noise. For each pixel, we firstly determine the adaptive window size by continuously enlarging the window size until the maximum and minimum values of two successive windows are equal respectively. Then the current pixel is regarded as noise candidate if it is equal to the maximum or minimum values, otherwise, it is regarded as noise-free pixel. Finally, the noise candidate is replaced by the weighted mean of the current window, while the noise-free pixel is left unchanged. Experiments and comparisons demonstrate that our proposed filter has very low detection error rate and high restoration quality especially for high-level noise.
Keywords :
adaptive filters; image denoising; image restoration; AWMF; adaptive weighted mean filter; adaptive window size; high-level noise; maximum values; minimum values; noise-free pixel; restoration quality; salt-and-pepper noise removal; Error analysis; Image restoration; Noise level; Noise measurement; PSNR; Signal processing algorithms; Filter; noise detection; salt and pepper noise;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2333012