Author(s)

B. Pradhan & S. Mansor

Abstract

Terrain data such as Light Detection and Ranging (LiDAR) compression has been an active research field for the last few years because of its large storage size. When LiDAR has a large number of data points, the surface generation represented by interpolation methods may be inefficient in both storage and computational requirements. This paper presents a newly developed compression scheme for the LiDAR data based on second generation wavelets. A new interpolation wavelet filter 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 the proposed technique is compared with the original LiDAR data. The results show that this method can be used for significant reduction of the data set. Keywords: Light Detection and Ranging (LiDAR), Delaunay triangulation, Triangulated Irregular Network (TIN), geographical information system, lifting scheme, second generation wavelets. 1 Introduction Recently, most of the methods for image compression are based on wavelets and related techniques. Wavelet approaches for image compression tend to outperform Fourier approaches because of their ability to represent both spatially localized features and smooth regions in an image. The superior compression capability of wavelets combined with their natural multiresolution structure

Keywords

Light Detection and Ranging (LiDAR), Delaunay triangulation, Triangulated Irregular Network (TIN), geographical information system, lifting scheme, second generation wavelets.