大区域地形数据的压缩与可视化

【作者】 杨宜进；

【导师】 孙怡；

【作者基本信息】 大连理工大学 ， 通信与信息系统， 2004， 硕士

【摘要】 随着地理信息系统(GIS)应用的不断深入，以二维方式处理三维空间数据已不能满足实际应用的需要。用户需要对他们的三维数据进行显示和分析。这就对三维GIS提出了发展要求。而在建立三维GIS的各个阶段中，就不可避免的要涉及到地形的三维可视化问题。另一方面，随着地形数据精度的提高，其数据量也在迅速增长。因此有必要对地形数据的压缩技术展开研究。 本文对地形三维可视化的研究是从两个方面展开的，即地表地形的三维可视化和地下三维可视化。在地表地形可视化方面，我们研究了两种常见的数字地形模型——规则格网和不规则三角网，总结它们各自的特点及生成算法，讨论了基于OpenGL、基于Java3D和基于ArcObjects的地形三维可视化的实现机制，最后给出了基于ArcObjects的三维地形飞行仿真系统的实现方法。在地下三维可视化方面，我们对体可视化过程中的切片级重建问题和体视见方法作了探讨，并实现了一个地下地质结构的三维展示系统。 在地形数据的压缩方面，我们首先对现有的栅格地形压缩算法作了分类，在研究了嵌入式零树小波编码算法及SPIHT算法的基础上，提出了基于图像子块所含细节多少的分块压缩算法。实验表明，该算法能获得比通常的编码压缩算法更高压缩率。在本文的最后，我们对三角网地形的生成算法、多分辨率地形模型以及ROAM算法做了探讨。更多还原

【Abstract】 With the extensive application of Geographic Information System (GIS), 2D GIS couldn’t meet the practical demands any longer. People want to visualize and analyze their three-dimensional data. This promotes the development of 3D GIS. However, visualization of terrain is inevitable during the course of building 3D GIS. Additionally, terrain data are becoming larger and larger along with the increase of accuracy. Therefore researches on visualization and compression of terrain data are of great importance.The researches on visualization of terrain fall into two parts: visualization of surface and visualization of underground space. In terms of visualization of surface, the features and constructing algorithms of GRID and TIN are summarized. Visualization based on OpenGL, Java3D and ArcObjects are discussed. Then a flyby simulation system based on ArcObjects is given as an example. In terms of visualization of underground space, surface reconstruction from planar contours and visibility determination are discussed. Subsequently, the realization of a 3D underground geologic demonstration system is given.In respect of compression of terrain, this paper classifies the existing compression algorithms and suggests a compression scheme on the basis of discussing EZW and SPIHT, This scheme utilizes the distribution of detail in the image. Experimental results prove that this compression scheme can achieve higher compression ratio than common algorithms. At the end of this paper, triangulation methods, mesh simplification and ROAM algorithm are discussed.更多还原