Morphological impulsive noise removal based on multi scale dual hit-or-miss transforms

Abstract

Impulsive noise removal is an active research area in optical signal processing. Morphological operators have been tried for impulsive noise removal. However, the performance is not very effective. Dual hit-or-miss transforms could identify the protruding bright or dark pixels like impulsive noise pixels in image, which may be used to construct effective algorithm for impulsive noise removal. In this paper, an algorithm based on the multi scale dual hit-or-miss transforms is demonstrated. Firstly, the positive impulsive noise pixels, which are bright pixels, are identified by multi scale hit-or-miss transform. Then, the negative impulsive noise pixels, which are dark pixels, are identified by multi scale dual hit-or-miss transform. Finally, the identified impulsive noise pixels are removed and replaced by a reasonable value estimated by adaptive median filter. Experimental results show that, because the multi scale dual hit-or-miss transforms could effectively and correctly identify the impulsive noise pixels, the noise pixels are correctly removed and the real image details could be well maintained.