A new approach to adaptive-neighborhood or region-based noise filtering is presented. The basic idea in this technique is to identify contextually related features in the image and to carry out statistical filtering operations using the pixels in these areas. Neighborhoods in the image are identified as sets of pixels that are 8-connected to the reference or seed pixel and are within a specified gray-level tolerance of the seed pixel. Thus, operations are based on contextual details in the image rather than an arbitrary grouping ofpixels (as in 3 x 3 filtering). These methods are applied to synthesized and natural images, and it is shown both quantitatively and qualitatively that adaptive-neighborhood filtering techniques are superior to analogous fixed-neighborhood filtering techniques.