Kernel density estimation based multichannel impulsive noise reduction filter

This paper presents a new filtering scheme for the removal of impulsive noise in multichannel images. It is based on the estimation of the probability density function for pixels in a filtering window, by means of the kernel density estimation method. The filtering algorithm itself is based on the comparison of pixels with their neighborhood in a sliding window. The results obtained with the new filter show its excellent ability to reduce impulsive noise while simultaneously preserving fine image details.