Abstract: A point cloud data set may be pre-processed for fast and efficient rendering. The pre-processing may comprise creating an octree hierarchy from the data, generating a level of detail (LOD) representation for each octree node, simplifying the points in each node according to a simplification tolerance, and storing the data structure in a file. Textures associated with each node may be stored in a separate, compressed file, such as a texture atlas. At render time, the octree and LOD hierarchy may be traversed until a suitable LOD node is found. The associated texture data may be accessed, and the node may be rendered as a textured quadrilateral and/or a splat point primitive. In an alternative approach, multiple point cloud datasets may be merged using a global transform function. The merged dataset may be simplified using a hierarchical LOD tree. Textures may be ascribed to each LOD node. The resulting structure may be rendered using splat and billboard point primitives.

Abstract: A lidar and digital camera system collect data and generate a three-dimensional image. A lidar generates a laser beam to form a lidar shot and to receive a reflected laser beam to provide range data. A digital camera includes an array of pixels to receive optical radiation and provide electro-optical data. An optical bench passes the laser beam, reflected laser beam, and optical radiation and is positioned to align each pixel to known positions within the lidar shot. Pixels are matched to form a lidar point-cloud which is used to generate an image.

Abstract: A 3-D model of a subject matter may be constructed from a plurality of lidar shots and overlapping EO images of the subject matter. Each of the lidar shots may be mapped to image patches within two or more of the EO images using navigation data associated with the lidar shots and EO images. Each of the back-projected lidar points may be set as a centroid of an image patch (collection of pixels) within an EO image. With the aid of the lidar centroids, the image patches in overlapping EO images may be correlated and an image-based pixel-to-pixel coordinate association therebetween may be calculated. Using this refined pixel-to-pixel coordinate association, a 3-D model of the subject matter may be constructed and refined using photogrammetry techniques. Videogrammetry techniques, such as optical flow techniques, may be applied if a sufficient amount of EO imagery data is available.

Abstract: A lidar and digital camera system collect data and generate a three-dimensional image. A lidar generates a laser beam to form a lidar shot and to receive a reflected laser beam to provide range data. A digital camera includes an array of pixels to receive optical radiation and provide electro-optical data. An optical bench passes the laser beam, reflected laser beam, and optical radiation and is positioned to align each pixel to known positions within the lidar shot. Pixels are matched to form a lidar point-cloud which is used to generate an image.

Abstract: A lidar and digital camera system collect data and generate a three-dimensional image. A lidar generates a laser beam to form a lidar shot and to receive a reflected laser beam to provide range data. A digital camera includes an array of pixels to receive optical radiation and provide electro-optical data. An optical bench passes the laser beam, reflected laser beam, and optical radiation and is positioned to align each pixel to known positions within the lidar shot. Pixels are matched to form a lidar point-cloud which is used to generate an image.

Abstract: A 3D MultiSpectral Lidar. The system comprises a laser transmitter light source, a laser detection assembly, optics that couple the outgoing and incoming laser signals, a digital camera assembly for collecting passive light, a position and orientation system, and processing hardware. The system provides real-time georectified three dimensional images and topography using an airborne platform. The system collects time-synchronous lidar range and image data in an optical receiver. The individual images are then mosaiced and orthorectified in real-time. The lidar range data and image data are then coupled to a position and orientation system to transform the three dimensional range images to a single geographically referenced multispectral three dimensional image.

Abstract: A 3D MultiSpectral Lidar. The system comprises a laser transmitter light source, a laser detection assembly, optics that couple the outgoing and incoming laser signals, a digital camera assembly for collecting passive light, a position and orientation system, and processing hardware. The system provides real-time georectified three dimensional images and topography using an airborne platform. The system collects time-synchronous lidar range and image data in an optical receiver. The individual images are then mosaiced and orthorectified in real-time. The lidar range data and image data are then coupled to a position and orientation system to transform the three dimensional range images to a single geographically referenced multispectral three dimensional image.