Mulitiresolution Spatial Data Compression Using Lifting Scheme

Abstract

In many applications referring to terrain visualization, there is need to visualize terrains at different levels of detail. The terrain should be visualized at different levels for different parts; for example, a region of high interest should be in a higher resolution than a region of low or no interest. The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the GIS data compression. A newly developed data compression approach to approximate the land surface with a series of non-overlapping triangle s has been presented. Over the years the TIN data representation has become a case in point for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. T his approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to ‘modify’ the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original terrain. The results show that this method can be used for significant reduction of data set.