Urban road extraction from high-resolution optical satellite images

Authors:
Mohamed Naouai;Atef Hamouda;Christiane Weber
Affiliations:
Faculty of Science of Tunis, University campus el Manar DSI, 2092 Tunis Belvédaire-Tunisia, Research unit URPAH;Faculty of Science of Tunis, University campus el Manar DSI, 2092 Tunis Belvédaire-Tunisia, Research unit URPAH;Laboratory Image Ville Environnement ERL 7230-CNRS-University Strasbourg, Strasbourg
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Year:
2010

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Abstract

Road extraction research has always been an active research on automatic identification of remote sensing images. With the availability of high spatial resolution images from new generation commercial sensors, how to extract roads quickly, accurately and automatically has been a cutting-edge problem in remote sensing related fields. In this paper, we present a novel road extraction approach which uses a scale space segmentation and two measures of the shape index to filter all regions from the result of the segmentation. The approach makes full use of spectral and geometric properties of roads in the imagery, and proposes a new algorithm named “Road Segments joint Algorithm” to ensure the continuity of roads.