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Road extraction from high-resolution remote sensing images using wavelet transform and hough transform

Road extraction from high-resolution remote sensing images has been a challenging problem in ground object detection field. In this paper, an effective and anti-noise road extraction method by using wavelet transform and Hough transform is proposed. Firstly, wavelet transform is used for image denoising and detecting edges of roads. Then the image is segmented into road area and non-road area. Hough transform is used to extract roads after segmentation. Finally, the effectiveness of the method is testified by the results of the experiment.