Road Extraction in SAR Images Using Genetic Algorithm
基于GA的SAR图像中主干道路提取

More and more attention has been paid to extraction of roads and other linear features from high-resolution synthetic aperture radar(SAR) images. Due to the complicated background of objectives and the speckle noise in the high-resolution SAR images, it is almost impossible to extract roads directly from original remote sensing images. In order to extract roads precisely from high-resolution SAR images with complicated background and speckle noise, a method of using genetic algorithm(GA) is developed to extract main roads in the paper. After the original SAR images are filtered to suppress the speckle noise, Fuzzy C means is used to classify the images unsupervisedly into vegetation, built areas, roads and other class, and the pixels belonging to the main roads are isolated from the images to simplify the original problem. Then, according to the membership of pixels to main roads and the uniformity of gray, a road model is constructed, and the genetic algorithm is used to search globally optimized roads. The experimental results show that the presented approach can effectively extract main roads from high-resolution SAR images.