LAUSR

Optical satellite remote sensing has become an important means of large-scale targets detection. However, due to the small perspective of satellite remote sensing, most of the structural information of slender targets, such as power transmission towers, is compressed during the imaging process. Experiments have found that the existing network does not work well in this situation. In order to tackle this problem, we proposed a shadow information-based slender targets detection (SI-STD) method. First, the shadow of the tower is used to compensate for the structure information lost during imaging. Second, the candidate regions containing towers and shadows are proposed by a modified regional proposal network (MRPN), which also classifies these regions at the same time. Third, the tower targets are regressed from candidate regions by TowerHead. Finally, by fusing the results of MRPN and TowerHead, we get the final results. The framework can comprehensively use the tower and its shadow to complete the detection task, and it has also shown excellent performance in the test.