Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images

0167-8655/$ see front matter 2009 Published by doi:10.1016/j.patrec.2009.12.018 * Corresponding author. Address: GIPSA-lab, Signa Institute of Technology, Grenoble, France. Fax: +33 4 E-mail addresses: [email protected] (S gipsa-lab.inpg.fr (J. Chanussot), [email protected] (J.A. Be (H. Talbot), [email protected] (B. Waske). Very high spatial resolution (VHR) images allow to feature man-made structures such as roads and thus enable their accurate analysis. Geometrical characteristics can be extracted using mathematical morphology. However, the prior choice of a reference shape (structuring element) introduces a shape-bias. This paper presents a new method for extracting roads in Very High Resolution remotely sensed images based on advanced directional morphological operators. The proposed approach introduces the use of Path Openings and Path Closings in order to extract structural pixel information. These morphological operators remain flexible enough to fit rectilinear and slightly curved structures since they do not depend on the choice of a structural element shape. As a consequence, they outperform standard approaches using rotating rectangular structuring elements. The method consists in building a granulometry chain using Path Openings and Path Closing to construct Morphological Profiles. For each pixel, the Morphological Profile constitutes the feature vector on which our road extraction is based. 2009 Published by Elsevier B.V.