Generalization of 3D building texture using image compression and multiple representation data structure

Textures are an essential part of 3D building models and often consume large portions of the data volume, thus making visualization difficult. Therefore, we propose a multi-resolution texture generalization method to compress the textures of 3D building models for dynamic visualization at different scales. It consists of two steps: image compression and texture coloring. In the first step, texture images are compressed using wavelet transformation in both the horizontal and the vertical direction. In the second step, a TextureTree is created to store building texture color for dynamic visualization from different distances. To generate a TextureTree, texture images are iteratively segmented by horizontal and vertical dividing zones, until each section is basically in the same color. Then the texture of each section is represented by their main color and the TextureTree is created based on the color difference between the adjacent sections. In dynamic visualization, the suitable compressed texture images or the TextureTree nodes are selected to generate 3D scenes based on the angle and the distance between the viewpoint and the building surface. The experimental results indicate that wavelet based image compression and the proposed TextureTree can effectively represent the visual features of the textured buildings with much less data.