in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Urbana-Champaign, Illinois, June 16-18 1992, pages 787-790.
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In this paper, we describe a new technique to produce a triangulated
irregular network (TIN) from a digital elevation model (DEM). The
overall goal is to produce an approximate terrain description that
preserves the major topographic features using a greatly reduced set
of points selected from the original DEM. The TIN generation process
is iterative; at each iteration we identify areas in the DEM that lie
outside of a user-supplied error tolerance in the TIN, and choose
points from the DEM to more accurately model these areas. Point
selection involves the computation of the difference between the
actual DEM and an approximate DEM. This approximate DEM is calculated
by interpolating elevation points from the TIN. The iterative nature of the algorithm permits users to terminate approximation algorithm based on operational criteria, such as median error, maximal error, or number of points used to construct the TIN. This is particularly relevant to real-time computer image generation as various scene rendering systems utilizing polygonal terrain patches have well defined limitations in order to maintain real-time performance. It also implies that the TIN generation procedure is automatically sensitive to smooth or rough terrain in that it selects only enough points to satisfy the required error constraints and tends to place points in those areas having the greatest topographic complexity.
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