LP360 is a family of tools for exploiting point clouds. The fundamental difference between an image and a point cloud is that the point cloud is a three dimensional representation of an environment whereas an image is a two dimensional representation (or, at best, a “two and a half” dimensional representation). A second major difference is that images are most typically represented using a uniform grid structure whereas a point cloud allows a non-uniform point (or “sample”) spacing. This difference is shown in Figure 1. Since the grid is a uniformly spaced structure, it is only necessary to store the values at the gird intersections (for example, Z for an elevation raster or Red-Green-Blue values for an image). The point cloud, on the other hand, has values that are randomly distributed and thus it is necessary to store all coordinates (for example, X, Y, Z and perhaps other values as well).
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