High probability impulse noise-removing algorithm based on mathematical morphology

A novel filter based on mathematical morphology for high probability impulse noise removal is presented. First, an impulse noise detector using mathematical residues is proposed to identify pixels that are contaminated by the salt or pepper noise. Then the image is restored using specialized open-close sequence algorithms that apply only to the noisy pixels. Finally, black and white blocks that degrade the quality of the image will be recovered by a block smart erase method. Experimental results demonstrate that the proposed filter outperforms a number of existing algorithms and is particularly effective for the very highly corrupted images.