Iterative TIN Generation from Digital Elevation Models

M. Polis and D. McKeown,

in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Urbana-Champaign, Illinois, June 16-18 1992, pages 787-790.


Abstract

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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