Anisotropy characterization of non stationary grey level textures

This communication deals with anisotropy characterization of grey level textures in a non stationary context. Three classes of characterization methods are tested. The first class of methods directly uses the non stationary data. We chose here the non stationary fractional Brownian motion (fBm) to model such images. The second class is based on a stationary approach. Thus, the image is to be stationarized first. The third class of methods is founded on stationary techniques too, but in a binary framework. For this reason, the original image must be stationarized and binarized first. All the proposed methods are tested on various grey level non stationary textures. Results show that all the techniques are in good agreement with the anisotropy visible on the data. The fBm based method is the only one that does not require any choice or adjustment of parameters. For a real application where the anisotropy really matters, this technique should be tested.