Locally constrained synthetic LoDs generation for natural terrain meshes

Terrain representation is a basic topic in the field of interactive graphics. The amount of data required for a good quality of the terrain offers an important challenge to developers of such systems. For users of these applications, the accuracy of geographical data is generally less important than its natural visual appearance. This makes it possible to maintain a limited geographical database for the system and to extend it generating synthetic data. The evaluation of the intrinsic properties of the terrain (i.e. fractal dimension, roughness, etc.) may be used as the basis for generating extra data accomplishing the same patterns discovered in the actual information. However, it is also interesting to point out that in most natural landscapes, it is usual to have human or natural changes in the basic properties of some areas, i.e. a road or a river. This fact can make it more difficult for synthetic data generation to be free of visual artifacts within these areas. In this paper, we combine fractal and wavelet theories to provide extra data which keeps the natural properties of actual information available. New levels of detail for the terrain are obtained by applying an inverse Wavelet Transform to a set of values randomly generated, thus maintaining the coherence of statistical properties with the original geographical data. Combined with this approach, the use of energy reduction masks has been added in order to avoid undesired visual artifacts in those special areas for which the general terrain properties are no longer valid.