Robust And Automatic Skyline Detection Algorithm Based On Mssdn

Automatic detection of the skyline plays an important role in several applications, such as visual geolocalization, flight control, port security, and mountain peak recognition. Existing skyline detection methods are mostly used under common weather conditions; however, they do not consider bad weather situations, such as rain, which limits their application in real scenes. In this paper, we propose a multi-streamstage DenseNet to detect skyline automatically under different weather conditions. This model fully considers the adverse factors influencing the skyline and outputs a probability graph of the skyline. Finally, a dynamic programming algorithm is implemented to detect the skyline in images accurately. A comparison with the existing state-of-the-art methods proves that the proposed model shows a good performance under rainy or common weather conditions and exhibits the best detection precision for the public database.