基于局部熵的高度场三角格网化研究

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泛的应用.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.由于我们通常对原始格网上的每一个点给出一个重要性度量,并以该度量值作为插入点选取的依据,因此重要性度量值计算方法的选取成为研究的重点.本文在对传统重要性度量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度量方法.实验结果表明,基于局部熵的插入点选取方法在各项性能上均优于局部误差估计的方法,并且有效的克服了以往方法中的"短视性"问题.

Height Field TIN Representation Based on Local Entropy

Because of its predominant capability,TIN (triangulated irregular network) has been widely used in the simplification of terrains represented as height field.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 measures has attained more and more attention.Based on analysis and comparison of traditional importance measures,we put forward a new importance measure based on local entropy.The results demonstrate that the local entropy criterion has a better performance than any traditional method.In addition,it can effectively conquer the "short sight" problem in previous methods.