The peergroup of an image pixel is a pixel similarity-based concept which has been successfully used to devise image denoising methods. However, since it is difficult to define the pixel similarity in a crisp way, we propose to represent this similarity in fuzzy terms. In this paper, we introduce the fuzzypeergroup concept, which extends the peergroup concept in the fuzzy setting. A fuzzypeergroup will be defined as a fuzzy set that takes a peergroup as support set and where the membership degree of each peergroup member will be given by its fuzzy similarity with respect to the pixel under processing. The fuzzypeergroup of each image pixel will be determined by means of a novel fuzzy logic-based procedure. We use the fuzzypeergroup concept to design a two-step color image filter cascading a fuzzy rule-based switching impulse noise filter by a fuzzy average filtering over the fuzzypeergroup. Both steps use the same fuzzypeergroup, which leads to computational savings. The proposed filter is able to efficiently suppress both Gaussian noise and impulse noise, as well as mixed Gaussian-impulse noise. Experimental results are provided to show that the proposed filter achieves a promising performance.