A Method for Automatic Road Extraction of High Resolution SAR Imagery

Nowadays automatic road extraction from satellite imageries is considered as one of the most important research trends in the field of remote sensing. This paper presents a method for automatic extraction of road centerlines from synthetic aperture radar (SAR) imagery. During the first step, three features, namely the direction of the least total radiance, the corresponding radiance, and the contrast are extracted to define the road characteristics by the backscatter coefficient of each pixel and its neighboring pixels from the SAR imagery. The fusion of the extracted features is carried out in the next step for detection of the road areas by using a fuzzy inference system. Afterwards, the morphology skeletonization is applied on the road areas to extract the road skeleton. Then some interested seed points are extracted so that they could be used in a snake model, which is employed to connect the seed points in order to form up the road centerlines. The proposed algorithm is tested on different parts of TerraSAR-X images. The experimental results reveal that the proposed method is effective in terms of correctness, completeness, and quality.

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