Color image enhancement based on nonparametric density estimation

This paper presents a new filtering scheme for the removal of impulsive noise in color images. It is based on estimating the probability density function for color 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 filter window. The quality of noise suppression and detail preservation of the new filter is measured quantitatively in terms of the standard image quality criteria. The filtering results obtained with the new filter show its excellent ability to reduce noise while simultaneously preserving fine image details.