The last generation of satellites leads to the very high-resolution images which offer a high quality of detailed information about the Earth's surface. However, the exploitation of such images becomes more complicated and less efficient as a consequence of the great heterogeneity of the objects displayed. In this paper, we address the problem of edge-preserving smoothing of high-resolution satellite images. We introduce a novel approach as a preprocessing step for feature extraction and/or image segmentation. The method we propose is related with the idea of resolution reduction and is derived from the multifractal formalism used for image compression. First, a multifractal decomposition scheme allows to extract the most singular transitions of the image. Then, an entropy-based criterium enables to consider a particular manifold composed with the most, simultaneously, relevant and singular pixels. Finally, a reconstruction scheme performed over this manifold provides an approxim...
Antonio Turiel, Hussein M. Yahia, Jacopo Grazzini