Fractal dimension estimation by adaptive mask selection

An algorithm is presented for solving conflicts between noise reduction and correct fractal dimension estimates. The basic idea has been derived from edge-preserving methods, which have been used for similar problems. Around each pixel, different masks are used; the most homogeneous neighborhood (in terms of fractal dimension) is then selected, and the fractal dimension D of the region is computed. An appropriate mask is selected for each pixel using an adaptive process, and, in particular, wide masks are used only for areas that do not exhibit any noticeable D variation