Research On Road Detection Of High Resolution Remote Sensing Image

As an important man-made object on the earth, the road has long been a subject of modern transportation system. Not only in the people’s living but also in the national’s economy, the road played a significant role. With the continuous and rapid development of remote sensing technology, it has become a main direction that how to use the computer technology to extraction roads from the vast amounts of remote sensing images quickly and efficiently. We mainly used mathematical morphology, path morphology and ring-projection algorithm to extract roads in high resolution remote sensing images.First of all, this dissertation used mathematical morphology method to extract the roads in the remote sensing images. The article combined the road’ features (brightness, size, and contrast) in remote sensing images with mathematical morphology operators such as reconstruction, hot-hat and so on, which formed an efficient method for road extraction. The experiment proved that the method can detect the road information in remote sensing images effectively.Secondly, the article used an extended mathematical morphology to extract the roads in high resolution remote sensing images. This method combined the path morphological with the method mentioned above to realize the road extraction in remote sensing images. Firstly this method extract the initial information of the road with the mathematical morphology mentioned above, then, add the path morphological and road geometrical constraints to the algorithm. The method can not only detect the roads, but also filter out the interference factors such as trees, buildings and bare soil. The experiment showed that roads can be extracted successfully.Finally, the thesis implemented a road detection algorithm based on ring-projection vector template matching in high resolution remote sensing images. The improved parameter settings which played a key role are more in line with the need of road extraction and optimized the ring-projection value and vector. To extract road center-line more precisely, we joined the center feature of circle into the ring-projection vectors and gave different weights to the vectors accordingly. The proposed method was applicable to detect twisty road and can detect the road center-line efficiently.