Automatic co-registration of satellite imagery and LiDAR data using local Mutual Information

Abstract

Automatic co-registration is a basic step in multi-sensor data fusion for remote sensing applications. The effectiveness of Mutual Information (MI) as a similarity measure for multi-sensor image registration has previously been reported for medical and remote sensing applications. In this paper, a new intensity-based approach built on local MI principles is presented. The approach decreases the complexity of higher dimension optimization by measuring local MI on well-distributed tie points. In addition, the reliability of registration is improved due to utilization of redundant observations of similarity. The performance of the proposed method for the registration of WorldView2 satellite imagery with LiDAR elevation and intensity data has been experimentally evaluated and the results obtained are presented.