Aerial Image Matching Algorithm Based on Edge Boxes

In the process of precisely locating targets using reconnaissance images from unmanned aerial vehicles (UAVs), the effectiveness of feature extraction is often hindered by the influence of rotation and perspective changes in UAV images. To address this issue, this study proposes an image matching method based on object block detection, dividing the matching problem into two key stages. In the object block detection stage, the Edge Boxes algorithm is employed to detect objects in the images. In the matching stage, the HardNet network is utilized for feature extraction from the detected object blocks, followed by similarity measurement. Experimental results demonstrate that this method achieves accurate image matching, overcoming challenges such as object rotation and small object extraction issues in UAV images. The proposed approach provides a feasible and effective means for UAV target localization.