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

doi:10.16182/j.issn1004731x.joss.201812013

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.

Key words: particle swarm optimization algorithm, volume rendering, viewpoint selection, 3D visualization

CLC Number:

TP391.9

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.

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