A road extraction method using beamlet transform

Synthetic Aperture Radar (SAR) systems have been widely used to estimate the various features on the ground. However, the images are often corrupted by noise that can impede further investigation of SAR images. Therefore, the extraction of features from SAR images with noisy backgrounds becomes a challenging issue in SAR image processing. The goal of this paper is to develop and implement a more robust method based on a beamlet transform to extract linear features such as roads from SAR images. The proposed method consists of three steps: First, an image pre-processing technique is used to offset the noise and low-contrast problems by recalculating the pixel values. Second, linear features such as road networks are then extracted by applying a beamlet transform based algorithm. In the third step, a post-processing algorithm is developed to analyze and link the discontinuities in order to connect the road networks in the image. Experimental results have demonstrated the effectiveness of this method.