Abstract: A geospatial imaging system may include a geospatial data storage device configured to store a geospatial dataset including geospatial data points. A processor may cooperate with the geospatial data storage device to determine segments within the geospatial dataset, with each segment including neighboring geospatial data points within the geospatial dataset sharing a common geometric characteristic from among different geometric characteristics. The processor may further determine border geospatial data points of adjacent segments, compare the border geospatial data points of the adjacent segments to determine bare earth segments having respective heights below those of the border geospatial data points of adjacent segments, and classify geospatial data points within each bare earth segment as bare earth geospatial data points.

Abstract: A geospatial imaging system may include a geospatial data storage device configured to store a geospatial dataset including geospatial data points. A processor may cooperate with the geospatial data storage device to determine segments within the geospatial dataset, with each segment including neighboring geospatial data points within the geospatial dataset sharing a common geometric characteristic from among different geometric characteristics. The processor may further determine border geospatial data points of adjacent segments, compare the border geospatial data points of the adjacent segments to determine bare earth segments having respective heights below those of the border geospatial data points of adjacent segments, and classify geospatial data points within each bare earth segment as bare earth geospatial data points.

Abstract: Method and system for registration of a two dimensional image data set and a three-dimensional image comprising point cloud data. The method begins by cropping a three-dimensional volume of point cloud data comprising a three-dimensional image data to remove a portion of the point cloud data comprising a ground surface within a scene, and dividing the three-dimensional volume into a plurality of m sub-volumes. Thereafter, the method continues by edge-enhancing a two-dimensional image data. Then, for each qualifying sub-volume, creating a filtered density image, calculating a two-dimensional correlation surface based on the filtered density image and the two-dimensional image data that has been edge enhanced, finding a peak of the two-dimensional correlation surface, determining a corresponding location of the peak within the two-dimensional image, defining a correspondence point set; and storing the correspondence point set in a point set list.

Abstract: Method and system for combining a 2D image with a 3D point cloud for improved visualization of a common scene as well as interpretation of the success of the registration process. The resulting fused data contains the combined information from the original 3D point cloud and the information from the 2D image. The original 3D point cloud data is color coded in accordance with a color map tagging process. By fusing data from different sensors, the resulting scene has several useful attributes relating to battle space awareness, target identification, change detection within a rendered scene, and determination of registration success.

Abstract: A system and method are provided for detecting surfaces in image data based on spatial data. The method includes obtaining an empirical probability density function (PDF) for the spatial data, where the spatial data includes a plurality of three-dimensional (3-D) point cloud data points associated with a plurality of default color space values. The method also includes generating a globally smooth estimated PDF based on the empirical PDF and a kernel smoothing technique, ascertaining one or more threshold elevation values for at least one mode in the estimated PDF, and tagging one or more portions of plurality of 3-D point cloud data points corresponding to the at least one mode based on the threshold elevation values.

Abstract: A geospatial modeling system may include a geospatial model database and a processor cooperating with the geospatial model database. The processor may be configured to determine void regions in a geospatial data set including foliage data points and bare earth data points, where each void region has a boundary and at least one bare earth data point therein. The processor may also be configured to inpaint additional bare earth data points into each void region based upon bare earth data points outside the boundary and the at least one bare earth data point therein.

Abstract: Systems and methods for improving visualization and interpretation of spatial data of a location are provided. In the method, a first radiometric image and three-dimensional (3-D) point cloud data registered (306) and the radiometric image is divided into a first plurality of image regions (308). Afterwards, one or more cloud data portions of the 3-D point cloud data associated with each of the first plurality of image regions are identified based on the registering (312). Portion color values, consisting of the region color values for corresponding ones of the first plurality of regions, are then applied to the cloud data portions (314). In some cases, an adjustment of the color values can be performed (318).

Abstract: A geospatial modeling system may include a geospatial data storage device, and a processor cooperating with the geospatial data storage device for selectively inpainting data into at least one void in geospatial model data using a partial differential equation (PDE) algorithm and an exemplar algorithm.

Abstract: A geospatial modeling system may include a geospatial model database and a processor. The processor may cooperate with the geospatial database for identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types. This may be done based upon applying multi-directional gradient calculations to the building roof data points.

Abstract: Method and system for registration of a two dimensional image data set and a three-dimensional image comprising point cloud data. The method begins by cropping a three-dimensional volume of point cloud data comprising a three-dimensional image data to remove a portion of the point cloud data comprising a ground surface within a scene, and dividing the three-dimensional volume into a plurality of m sub-volumes. Thereafter, the method continues by edge-enhancing a two-dimensional image data. Then, for each qualifying sub-volume, creating a filtered density image, calculating a two-dimensional correlation surface based on the filtered density image and the two-dimensional image data that has been edge enhanced, finding a peak of the two-dimensional correlation surface, determining a corresponding location of the peak within the two-dimensional image, defining a correspondence point set; and storing the correspondence point set in a point set list.

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 and system for combining a 2D image with a 3D point cloud for improved visualization of a common scene as well as interpretation of the success of the registration process. The resulting fused data contains the combined information from the original 3D point cloud and the information from the 2D image. The original 3D point cloud data is color coded in accordance with a color map tagging process. By fusing data from different sensors, the resulting scene has several useful attributes relating to battle space awareness, target identification, change detection within a rendered scene, and determination of registration success.

Abstract: A geospatial modeling system may include a geospatial model database and a processor. The processor may cooperate with the geospatial model database for inpainting data into at least one void in geospatial model terrain data based upon propagating contour data from outside the at least one void into the at least one void.

Abstract: A geospatial modeling system may include a geospatial model database and a processor. More particularly, the processor may cooperate with the geospatial model database for inpainting data into at least one void in geospatial model frequency domain data based upon propagating contour data from outside the at least one void into the at least one void, and for converting the geospatial model frequency domain data after inpainting into geospatial model spatial domain data.

Abstract: A geospatial modeling system may include a geospatial model database and a processor. The processor may cooperate with the geospatial database for identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types. This may be done based upon applying multi-directional gradient calculations to the building roof data points.

Abstract: A geospatial modeling system may include a geospatial model database and a processor. More particularly, the processor may cooperate with the geospatial model database for inpainting data into at least one void in geospatial model cultural feature data based upon propagating contour data from outside the at least one void into the at least one void.

Abstract: A geospatial modeling system may include a geospatial model database and a processor cooperating therewith for filtering geospatial model data. This may be done by selectively updating a target point based upon adjacent points lying along a plurality of radial line segments extending outwardly from the at least one target point.

Abstract: A geospatial modeling system may include a geospatial model database containing geospatial model data, a display, and a processor. The processor may cooperate with the geospatial model database and the display for determining a respective group of tree crown vegetation points from the geospatial model data for each tree of a plurality of trees, and for displaying a respective simulated tree trunk beneath each group of tree crown vegetation points. The processor may generate each simulated tree trunk to have a tree trunk height based upon heights of the respective group of tree crown vegetation points.

Abstract: A geospatial modeling system may include a geospatial model database and a processor cooperating therewith for performing at least one noise filtering operation on data comprising elevations associated with respective location points. The at least one noise filtering operation may include determining a respective center point elevation difference for each location point and based upon a sum of differences between elevations of a given location point and a plurality of neighboring location points.

Abstract: A geospatial modeling system may include a geospatial data storage device, and a processor cooperating with the geospatial data storage device for selectively inpainting data into at least one void in geospatial model data using a partial differential equation (PDE) algorithm and an exemplar algorithm.