Map-enhanced uav image sequence registration

Registering consecutive images from an airborne sensor into a mosaic is an essential tool for image analysts. Strictly local methods tend to accumulate errors, resulting in distor-tion. We propose here to use a reference image (such as a high resolution map image) to overcome this limitation. In our approach, we register a frame in an image sequence to the map using both frame-to-frame registration and frame-to-map registration iteratively. In frame-to-frame registra-tion, a frame is registered to its previous frame. With its previous frame been registered to the map in the previous iteration, we can derive an estimated transformation from the frame to the map. In frame-to-map registration, we warp the frame to the map by this transformation to com-pensate for scale and rotation difference and then perform an area based matching using Mutual Information to find correspondences between this warped frame and the map. These correspondences together with the correspondences in previous frames could be regarded as correspondences between the partial local mosaic and the map. By register-ing the partial local mosaic to the map, we derive a trans-formation from the frame to the map. With this two-step registration, the errors between each consecutive frames are not accumulated. We then extend our approach to synchro-nize multiple image sequences by tracking moving objects in each image sequence, and aligning the frames based on the object’s coordinates in the reference image. 1