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

  • Authors:

  • Silvia Valero;Jocelyn Chanussot;Jon Atli Benediktsson;Hugues Talbot;Bjorn Waske

  • Affiliations:

  • GIPSA-lab, Signal & Image Dept., Grenoble Institute of Technology, Grenoble, France and Dept. of Electrical and Computer Engineering, University of Iceland, Raykjavik, Iceland;GIPSA-lab, Signal & Image Dept., Grenoble Institute of Technology, Grenoble, France;Dept. of Electrical and Computer Engineering, University of Iceland, Raykjavik, Iceland;IGM, A2SI, ESIEE, Noisy-le-Grand, France;Dept. of Electrical and Computer Engineering, University of Iceland, Raykjavik, Iceland

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 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 and hence outperform standar approaches using rotating rectangular structuring elements. The method consists in building a granulometry chain using Path Openings and Closing to perform Morphological Profiles. For each pixel, the Morphological Profile constitutes the feature vector on which out road extraction is based.