Geo-registration of Aerial Images by Feature Matching

摘要

In this paper, we propose a new featured-based geo-registration technique for aerial images that helps nearly real-timely calibrate and update the telemetry data and sensor model on flight. Firstly by using the available telemetry information, we bring both images into a common projection space. Second, we use the distribution of local geometric properties to guess the initial rotation and translation parameters. After the coarse alignment, the Harris operator is adopted to produce the initial feature points set, while the corresponding feature points set in the target image can be established through normalized correlation in local neighborhood of the selected points' position. Finally after the matched feature point sets are well constructed, the transform parameters can be solved by least square error estimation. The experiment shows our algorithm can effectively reduce the error in telemetry data caused by various noises.