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Noise is an important factor that influences image quality, which is mainly produced in the processes of image acquirement and transmission. Noise reduction is necessary for us to do image processing and image interpretation so as to acquire useful information that we want. This paper presents a novel approach to the problem of noise reduction for PGM images. The proposed technique is based on the maximization of the similarities between pixels in the filtering window. The method is able to remove the noise component, while adapting itself to the local image structure. In this way, the proposed algorithm eliminates impulsive noise while preserving edges and fine image details. Since the algorithm can be considered as a modification of the vector median filter driven by fuzzy membership functions, it is fast, computationally efficient, and easy to implement. Simulation results show that the proposed fuzzy filter effectively removes the noise by preserving image originality.