基于熵特征的快速格网逼近

不规则三角格网表示以其优越的性能在地形高度场数据的简化中得到了广州应用。在不规则三角格网生成的过程中,插入点的选取是关系到最终简化后的地形逼近质量好坏的关键。由于通常将在每一个点上计算得到的重要性测度作为插入点选取的依据,因此重要性测度准则的选取成为研究的重点。文中在对传统重要性测度计算方法的性能比较和分析基础上,提出了一种基于局部熵的重要性测度计算准则。实验结果表明,基于局部熵准则的插入点选取方法在各项性能上均优于传统的方法,并且有效地克服了以往方法中的“短视性”问题。

Fast TIN approximation based on entropy feature

Triangulated Irregular Network (TIN) has been widely used in the simplification of terrains represented as height field because of its predominant capability. During the generation of TIN, selection of input points is the key to the approximation quality of simplified terrains. Usually, the input point is selected according to the importance measure on each point, so research on the calculation of importance measure has attained more and more attention. Based on analysis and comparison of traditional importance measure, a new criterion of importance measure based on local entropy is put forward. The results demonstrate that the local entropy criterion gives a performance that is better than any traditional method. In addition, it can effectively conquer the "short sight" problem in previous methods.