In image analysis, most problems arise from the segmentation process. These problems notably increase when one has to work on SAR images, due to the speckle noise affecting this kind of data. A large number of filters have been proposed in order to reduce speckle, but results are not satisfactory in all cases. The idea suggested in this paper is to by-pass the speckle drawback by performing segmentation not only on physical data but also on virtual ones. The latter are derived from the former through some processing step (e.g., textural analysis). Segmentation is then achieved by analyzing these different data simultaneously, thus recovering uncertain situations. Some results are reported and discussed: they evidence the high performances allowed by this approach, even when speckle noise is not reduced.