LiDAR Point Cloud and Stereo Image Point Cloud Fusion
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
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The advent of Light Detection and Ranging LiDAR point cloud collection has significantly improved the ability to model the world in precise, fine, three-dimensional details. The objective of this research was to demonstrate accurate, foundation methods for fusing LiDAR data and photogrammetric imagery and their potential for change detection. The scope of the project was to investigate optical image to LiDAR registration methods, focusing on several dissimilar image types including Optical Bar Camera OBC, high resolution aerial frame, and WorldView 1 satellite with varying LiDAR point densities. An innovative optical image to LiDAR data registration process was established. This approach was demonstrated for one image type using the rational polynomial coefficients RPC representation of the panoramic math model improving accuracy from 1.9 m to 0.5 m root mean square RMS error. Comparison of stereo imagery point cloud data to the LiDAR point cloud using a 90 confidence interval highlighted changes that included small scale 50cm, sensor dependent change and large scale, new home construction change. This research also proposed a fused LiDAR and stereo image base layer as the foundation for further LiDARimage fusion.
- Optical Detection and Detectors