关键词: 加权中值滤波, 噪声检测, 修剪中值, 灰度最值, 加权系数, 相关性

Abstract: Aims at overcoming the defects of existing filters in noise detection and noise removal, this paper proposes an adaptive weighted median filtering algorithm based on detection with trimmed median. This filter first performs noise detection by using the minimum and maximum intensities, namely 0 and 255, which makes full use of the intensity characteristics of impulse noise, and then performs further noise detection based on the correlation and the approximation in intensity among neighboring pixels. And on the basis that the correlation among neighboring pixels decreases with the increasing of distance, different weighted coefficients are given to the noise free pixels at different distance in the neighborhood, the weighted median is used to remove noise. The size of neighborhood for denoising varies adaptively along with noise densities. Simulation results and analysis prove that the proposed method is capable of denoising effectively. Its denoising performance has outperformed significantly the existing distinguished filters in terms of peak signal to noise ratio, image enhancement factor and visual representation, especially for removing high density noise, it shows significant superiority over other filters.

Key words: weighted median filter, noise detection, trimmed median, minimum and maximum intensities, weighted coefficient, correlation