The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-1/W5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 583–587, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-583-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 583–587, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-583-2015

  11 Dec 2015

11 Dec 2015

AUTOMATIC ROAD EXTRACTION BASED ON INTEGRATION OF HIGH RESOLUTION LIDAR AND AERIAL IMAGERY

S. Rahimi1, H. Arefi1, and R. Bahmanyar2 S. Rahimi et al.
  • 1School of Surveying and Geospatial Engineering, University of Tehran, Tehran, Iran
  • 2Institute of Remote Sensing Technology (IMF), German Aerospace Center (DLR), Wessling, Germany

Keywords: Automatic Road Extraction, High Resolution Aerial Imagery, Hough Transform, LiDAR, Principal Component Analysis

Abstract. In recent years, the rapid increase in the demand for road information together with the availability of large volumes of high resolution Earth Observation (EO) images, have drawn remarkable interest to the use of EO images for road extraction. Among the proposed methods, the unsupervised fully-automatic ones are more efficient since they do not require human effort. Considering the proposed methods, the focus is usually to improve the road network detection, while the roads’ precise delineation has been less attended to. In this paper, we propose a new unsupervised fully-automatic road extraction method, based on the integration of the high resolution LiDAR and aerial images of a scene using Principal Component Analysis (PCA). This method discriminates the existing roads in a scene; and then precisely delineates them. Hough transform is then applied to the integrated information to extract straight lines; which are further used to segment the scene and discriminate the existing roads. The roads’ edges are then precisely localized using a projection-based technique, and the round corners are further refined. Experimental results demonstrate that our proposed method extracts and delineates the roads with a high accuracy.