A Fast and Robust UAV Images Mosaic Method

Unmanned Aerial Vehicle (UAV) can respond quickly and provide image data at the first time in mapping support tasks, such as battlefield environment monitoring and natural disaster damage assessment. However, UAV is prone to fast flight speed and poor attitude stability, which brings a new challenge to image mosaic relying on feature matching. In this paper, an efficient and robust UAV image mosaic method is proposed. The main idea is to take graph theory and POS data to image mosaic process. Firstly, we estimate the range of aerial photography based on POS data, and construct the UAV images relationship diagram. Then, according to the attitude information, the images in relation set are divided into stable group and disturbance group, and the image classification connection graph is generated. By defining the weighted topological graph and constructing the minimum spanning tree, we search key frames and reference image. Finally, we derive the homography matrix between adjacent images according to imaging model. The mosaic image is generated after global registration and images fusion. Experimental results show that our proposed approach can solve the mosaic problems of narrow overlap and texture deficient images, and produce superior results in reducing projection distortion and shortening registration time consumption.