自适应可调混沌粒子群算法的体绘制视点选择（英文）  

Volume Rendering Viewpoint Selection Based on Adaptive Scaleable Chaotic Particle Swarm Optimization

作　　者：曾艳阳[1] 张泽浩 冯云霞 Zeng Yanyang;Zhang Zehao;Feng Yunxia(College of Computer Science and Technology of Henau Polytechnic University,Jiaozuo 454000,China)

机构地区：[1]河南理工大学计算机科学与技术学院,河南焦作454000

出　　处：《系统仿真学报》2018年第12期4595-4601,共7页Journal of System Simulation

基　　金：National Natural Science Foundation of China(61503124)

摘　　要：人们常通过人工试探的方法进行体绘制视点选择,然而当体数据较多时往往花费大量的时间而降低效率。提出将自适应可调的混沌粒子群优化算法用于体绘制中视点的自动选择。该算法引入图像信息熵来评估在不同视点处对应的图像的质量。熵值作为视点优化的依据和粒子群优化的适应度值,从而实现了智能化和自动化的选择,最终得到最佳视点。People often perform volume rendering viewpoint selection by means of manual exploration. However,when the volume data is large,it often takes a lot of time to reduce the efficiency.An adaptive scaling chaotic particle swarm optimization algorithm is proposed for the automatic selection of viewpoints in volume rendering.The algorithm introduces image information entropy to evaluate the quality of images corresponding at different viewpoints.The entropy value is used as the basis for optimizing the viewpoint and the fitness value of the particle swarm optimization,so as to realize the intelligent and automatic choice,and finally obtain the best viewpoint.

关 键 词：粒子群优化算法 体绘制 视点选择 三维可视化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]