Automatic extraction of Irregular Network digital terrain models

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Abstract
For representation of terrain, an efficient alternative to dense grids is the Triangulated Irregular Network (TIN), which represents a surface as a set of non-overlapping contiguous triangular facets, of irregular size and shape. The source of digital terrain data is increasingly dense raster models produced by automated orthophoto machines or by direct sensors such as synthetic aperture radar. A method is described for automatically extracting a TIN model from dense raster data. An initial approximation is constructed by automatically triangulating a set of feature points derived from the raster model. The method works by local incremental refinement of this model by the addition of new points until a uniform approximation of specified tolerance is obtained. Empirical results show that substantial savings in storage can be obtained.

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