TY - JOUR
T1 - Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images
AU - Valero, S.
AU - Chanussot, J.
AU - Benediktsson, J. A.
AU - Talbot, H.
AU - Waske, B.
PY - 2010/7/15
Y1 - 2010/7/15
N2 - 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.
AB - 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.
KW - Mathematical morphology
KW - Morphological Profiles
KW - Path Openings and Closings
KW - Road extraction
UR - http://www.scopus.com/inward/record.url?scp=77953139504&partnerID=8YFLogxK
U2 - 10.1016/j.patrec.2009.12.018
DO - 10.1016/j.patrec.2009.12.018
M3 - Article
AN - SCOPUS:77953139504
SN - 0167-8655
VL - 31
SP - 1120
EP - 1127
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
IS - 10
ER -