Automatic registration of optical imagery with 3d lidar data using local combined mutual information
Other literature type, Article
Parmehr, E. G.
Fraser, C. S.
- Publisher: Copernicus Publications
(issn: 2194-9050, eissn: 2194-9050)
TA1-2040 | T | TA1501-1820 | Applied optics. Photonics | Engineering (General). Civil engineering (General) | Technology
Automatic registration of multi-sensor data is a basic step in data fusion for photogrammetric and remote sensing applications. The
effectiveness of intensity-based methods such as Mutual Information (MI) for automated registration of multi-sensor image has been
previously reported for medical and remote sensing applications. In this paper, a new multivariable MI approach that exploits
complementary information of inherently registered LiDAR DSM and intensity data to improve the robustness of registering optical
imagery and LiDAR point cloud, is presented. LiDAR DSM and intensity information has been utilised in measuring the similarity
of LiDAR and optical imagery via the Combined MI. An effective histogramming technique is adopted to facilitate estimation of a
3D probability density function (pdf). In addition, a local similarity measure is introduced to decrease the complexity of optimisation
at higher dimensions and computation cost. Therefore, the reliability of registration is improved due to the use of redundant
observations of similarity. The performance of the proposed method for registration of satellite and aerial images with LiDAR data in
urban and rural areas is experimentally evaluated and the results obtained are discussed.