Abstract: Systems and methods for associating color with spatial data are provided. In the system and method, a scene tag is selected for a portion 804 of a radiometric image data (800) of a location and a portion of the spatial data (200) associated with the first portion of the radiometric image data is selected. Based on the scene tag, a color space function (500, 600) for the portion of the spatial data is selected, where the color space function defines hue, saturation, and intensity (HSI) values as a function of an altitude coordinate of the spatial data. The portion of the spatial data is displayed using the HSI values selected from the color space function based on the portion of the spatial data. In the system and method, scene tags are each associated different classifications, where each color space function represents a different pre-defined variation in the HSI values for an associated classification.

Abstract: Method for providing a color representation of three-dimensional range data (200) for improved visualization and interpretation. The method also includes selectively determining respective values of the hue (402), saturation (404), and intensity (406) in accordance with a color map (FIG. 5, 6) for mapping the hue, saturation, and intensity to an altitude coordinate of the three-dimensional range data. The color map is defined so that values for the saturation and the intensity have a first peak value at a first predetermined altitude approximately corresponding to an upper height limit (308) of a predetermined target height range (306). Values defined for the saturation and the intensity have a second peak at a second predetermined altitude (310) corresponding to an approximate anticipated height of tree tops within a natural scene.

Abstract: Method (300) for registration of n frames 3D point cloud data. Frame pairs (200i, 200j) are selected from among the n frames and sub-volumes (702) within each frame are defined. Qualifying sub-volumes are identified in which the 3D point cloud data has a blob-like structure. A location of a centroid associated with each of the blob-like objects is also determined. Correspondence points between frame pairs are determined using the locations of the centroids in corresponding sub-volumes of different frames. Thereafter, the correspondence points are used to simultaneously calculate for all n frames, global translation and rotation vectors for registering all points in each frame. Data points in the n frames are then transformed using the global translation and rotation vectors to provide a set of n coarsely adjusted frames.