A speckle reduction algorithm, the Edge Map-Directed Adaptive Mean (EMDAM) filter, is studied in this paper. It adapts the ordinary mean filter according to the scene heterogeneity. Edge-crossing maps determined by an edge detector are used to find the largest homogeneous subregion in the moving filter window. Then, the mean filter is adapted only to this homogeneous part of the moving filter window and applied if no edge crossing is found. We compared some filters in the literature to the EMDAM filter using two examples: a 1997 JERS-1 synthetic aperture radar (SAR) image of Tuzla, Istanbul and a computer-simulated SAR image. The filter performance was assessed both quantitatively and qualitatively. We found that the EMDAM filter preserves textures and details while reducing speckle to a desired level. A new testing quantity, the Quality Factor (Q), is also introduced.