High-resolution Dem Generation Using Self-consistency

We present a practical method for producing a high-resolution digital elevation map (DEM) from a set of spatially overlapping images. We start with the principle that multiple low-resolution DEMs can be combined to form a high-resolution DEM provided that (i) the sample DEMs are registered to the same coordinate system; (ii) the elevation estimates at each posting are partially independent; and (iii) the elevation errors between postings within a DEM are partially independent. Under these conditions, each sample DEM contributes an incremental amount of new information to the composite DEM. As a result, increasing the number of sample DEMs will increase the spatial resolution as well as decrease its vertical error bounds of the composite DEM. The key to an effective implementation of this algorithm is the ability to produce sample DEMs which are free from large blunders. We are able to separate valid elevation estimates from blunders by exploiting their uniquely statistical properties. In general elevation estimates (computed by image matching algorithms) are members of one of two populations: Valid estimates in which the image matching algorithm identified a pair of corresponding pixels (one in the reference image and one in the target image) that are projections of the same surface point; and blunders in which the image matching algorithm identified corresponding pixels that are not projections of the same surface point. Since blunders are not related to the surface, corresponding pixels can occur anywhere in the search range. As a result, valid elevation estimates have an error distribution characterized by an unbiased normal distribution with a small standard deviation, and (ii) blunders have an error distribution characterized by a uniform distribution spread out over a much larger range. The standard deviation of the valid error distribution corresponds to the elevation range seen by a single pixel; whereas, the width of the blunder distribution corresponds to the full search range.