Introduction to 2.5-D Visualization
2.5-D visualization (sometimes referred to as HeightMap or DepthMap visualization) is a hybrid of 2-D and 3-D visualization.
By taking a 2-D dataset with some type of elevation value at each point, this elevation can be directly mapped onto the missing 3rd dimension to create a 3-D visualization. This is frequently used for terrain maps. This is also the foundation of several optimization algorithms such as real-time optimally adapting mesh (ROAM) - a level of detail algorithm.
- Space - Such data can easily be stored as compressed grayscale images, utilizing widespread and highly developed compression schemes such as JPG or PNG.
- Performance - Certain assumptions can be made about this data to remove certain penalizing conditions (overlapping geometry, etc.).
- Simplicity - Since the data is inherently 2-dimensional, most 2-dimensional algorithms can be used to manipulate it (mostly). Decimation and feature detection in 2-dimensions is significantly easier than in 3-dimensions.
- Geometry Restrictions - Since only a single Z value can exist at every X & Y coordinate, overlapping geometry is impossible.