Viewpoint Selection Using Hybrid Simplex Search and Particle Swarm Optimization for Volume Rendering

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Author(s)

Zhang You-Sai 1,* Dai Chang-jiang 1 Wang Bin 2 Zhu Zhi-yu 1

1. Jiangsu University of Science and Technology, Zhenjiang, China

2. Elekta (Shanghai) Instruments Ltd, Shanghai, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2012.09.03

Received: 11 May 2012 / Revised: 29 Jun. 2012 / Accepted: 10 Aug. 2012 / Published: 8 Sep. 2012

Index Terms

Volume rendering, Viewpoint selection, Simplex search, Particle swarm optimization, Viewpoint entropy

Abstract

In this paper we proposed a novel method of viewpoint selection using the hybrid Nelder-Mead (NM) simplex search and particle swarm optimization (PSO) to improve the efficiency and the intelligent level of volume rendering. This method constructed the viewpoint quality evaluation function in the form of entropy by utilizing the luminance and structure features of the two-dimensional projective image of volume data. During the process of volume rendering, the hybrid NM-PSO algorithm intended to locate the globally optimal viewpoint or a set of the optimized viewpoints automatically and intelligently. Experimental results have shown that this method avoids redundant interactions and evidently improves the efficiency of volume rendering. The optimized viewpoints can focus on the important structural features or the region of interest in volume data and exhibit definite correlation with the perception character of human visual system. Compared with the methods based on PSO or NM simplex search, our method has the better performance of convergence rate, convergence accuracy and robustness.

Cite This Paper

Zhang You-sai,Dai Chang-jiang,Wang Bin,Zhu Zhi-yu,"Viewpoint Selection Using Hybrid Simplex Search and Particle Swarm Optimization for Volume Rendering", IJIGSP, vol.4, no.9, pp.17-22, 2012. DOI: 10.5815/ijigsp.2012.09.03

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