Impulse noise removal based on long-range correlation in an image

Images are often contaminated by impulse noise. The major drawback of median filtering and its variants -that are widely used for removing impulsive noise- is the blurring effect for large window sizes and low noise suppression for small window sizes. In this paper, an algorithm for removing impulse noise in images is proposed. The long-range correlation information in a competitive scheme is utilized to find the gray level of degraded pixels. The experimental results show that the performance of our method in removing impulse noise is better than that of most other state-of-the-art methods.