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Article Dans Une Revue Pattern Recognition Letters Année : 2010

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

Résumé

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.
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Dates et versions

hal-00578852 , version 1 (27-03-2011)

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Silvia Valero, Jocelyn Chanussot, Jon Atli Benediktsson, Hugues Talbot, Bjorn Waske. Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images. Pattern Recognition Letters, 2010, 31 (10), pp.1120-1127. ⟨10.1016/j.patrec.2009.12.018⟩. ⟨hal-00578852⟩
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