In the paper, a novel approach to the enhancement of color images corrupted by impulsive noise is presented. The proposed algorithm first calculates for every image pixel the distances in the RGB color space to all elements belonging to the filtering window. Then, a sum of a specified number of smallest distances, which serves as a measure of pixel similarity, is calculated. This generalization of the Rank-Ordered Absolute Difference (ROAD) is robust to outliers, as the high distances are not considered when calculating this measure. Next, for each pixel, a neighbor with smallest ROAD value is searched for. If such a pixel is found, then the filtering window is moved to a new position and again a neighbor, with ROAD measure lower than the initial value is looked for. If it is encountered, the window is moved again, otherwise the process is terminated and the starting pixel is replaced with the last pixel in the path formed by the iterative procedure of the window shifting. The comparison with the filters intended for the removal of noise in color images revealed excellent properties of the new enhancement technique. It is very fast, as the ROAD values can be pre-computed, and the formation of the paths needs only comparisons of scalar values. The proposed technique can be applied for the restoration of color images distorted by impulsive noise and can also be used as a method of edge sharpening. Its low computational complexity allows also for its application in the processing of video sequences.