Stabilization and Mosaicing of Airborne Videos

We present an algorithm for stabilizing low-quality and low-resolution video sequences obtained from UAVs and MAVs flying over a predominantly planar terrain. The problem is important for the processing of videos captured from airborne platforms where most of the image region gives little information about the image-motion. The algorithm consists of approximately aligning the images using phase correlation, then refining the transformation parameters using available optical flow measurements and finally performing a minimization of the image difference by carefully selecting the image regions to make the iterations converge. In the second part of the paper, we describe an algorithm for camera ego-motion estimation by incorporating available metadata along with the video sequence. The availability of metadata such as IMU measurements provides a good initial solution for the camera orientation and helps the iterations converge faster by reducing the search space.