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

Authors

Yanyang Zeng, College of Computer Science and Technology of Henan Polytechnic University, Jiaozuo 454000, China;
Zehao Zhang, College of Computer Science and Technology of Henan Polytechnic University, Jiaozuo 454000, China;
Yunxia Feng, College of Computer Science and Technology of Henan Polytechnic University, Jiaozuo 454000, China;

Abstract

Abstract: 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.

Recommended Citation

Zeng, Yanyang; Zhang, Zehao; and Feng, Yunxia (2019) "Volume Rendering Viewpoint Selection Based on Adaptive Scaleable Chaotic Particle Swarm Optimization," Journal of System Simulation: Vol. 30: Iss. 12, Article 13.
DOI: 10.16182/j.issn1004731x.joss.201812013
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss12/13

First Page

4595

Revised Date

2018-06-15

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201812013

Last Page

4601

CLC

TP391.9

Recommended Citation

Zeng Yanyang, Zhang Zehao, Feng Yunxia. Volume Rendering Viewpoint Selection Based on Adaptive Scaleable Chaotic Particle Swarm Optimization[J]. Journal of System Simulation, 2018, 30(12): 4595-4601.

DOI

10.16182/j.issn1004731x.joss.201812013