一种新的基于发散度函数的地形模型简化方法

提出了一种新的地形模型简化方法,该方法是在隐式四叉树层次结构基础上,结合离散粒子群思想建立地形的简化模型.文中重新定义粒子为具有层次信息的特征点的集合,从而每个粒子与简化模型的一个候选解相对应.为了实现多个粒子的空间压缩和快速检索,给出了隐式四叉树层次结构的快速索引方法.此外提出了基于法向矢量夹角的发散度函数的误差计算方法,重新定义了既满足地形模型误差要求同时兼顾模型简化比例的粒子评价函数,使地形简化模型在保持细节特征和轮廓特征的同时获得了更优的简化比率和模型精度.最后采用最优粒子作为启发信息引导简化过程,因此多个粒子迅速收敛于最优简化模型,从而模型的简化效率大大提高.文中方法均在多个基准数据上进行实验研究,结果表明与经典层次简化方法相比,算法效率和模型精度均显著提高.

A New Simplification Method for Terrain Model Based on Divergence Function

This paper presents a fast simplification method for the terrain model using the discrete particle swarm algorithm based on the quad-tree hierarchical structure.What is new in this paper is that the particle has been redefined as a set of feature points.And then each particle presents a candidate solution of the approximation model.In order to compress those particles,a connotative quad-tree hierarchical structure and its index technology are proposed in this paper.Usually,an error measure is very important...