Robust airplane detection in satellite images

Automatic target detection in satellite images remains a challenging problem. The main difficulties lie in the cooccurrence of variations of target type, pose, and size in huge satellite image. In this paper, we propose a new airplane detection approach based on visual saliency computation and symmetry detection. The advantages are twofold. First, saliency and symmetry detection perform stably in obtaining target location and orientation information. Second, independent of target type, pose and size, saliency map and symmetry detection are computed only once. This saves a large amount of computational time but does not miss any targets. Experiments show that our method provides a promising way to detect airplanes in complex airport scenes.