Vision-based horizon extraction method under Kalman Filter framework

As the demands of UAV´s visual navigation technology, we bring out a new horizon extraction method in this paper. Firstly, we propose a horizon extraction algorithm for single image. We employ dark channel in single image to avoid the interferences from clouds and fogs, and use Sobel operator extract edges, among which we can extract the true horizon through an algorithm mentioned in Paragraph II. Secondly, we propose a horizon extraction algorithm for video streaming under Kalman Filter (KF) framework based on the horizon extraction algorism for single image. The position of horizon in each frame will be estimated by using the priori horizon positions under KF framework at first, and a search neighborhood will be determined around the estimated position, in which we can get the true position of the horizon through a certain search algorithm. Simulations and analyses are carried out with aerial video streaming, the results show that such algorithms work well on those videos with noise, clouds and fogs, while the time overhead decrease by about 50% than traditional algorithms.