关键词: 三维可视化, 视点优化, 粒子群算法, 图像信息熵

Abstract: To choose the best viewpoint of 3D visualization, the commonly used artificial temptation usually leads to problems of increase of iteration number and poor design efficiency. Therefore, the algorithm based on particle swarm optimization is proposed for viewpoint optimization. The algorithm expresses the viewpoint by using multi-resolution level, and introduces image information entropy for evaluating the quality of the rendered 3D image at different viewpoints. The value of entropy is as the basis of viewpoint optimization and the fitness value of particle swarm optimization. It achieves the intelligent and automatic optimization for viewpoints from the 3D visualization by using the particle swarm optimization algorithm, and thus to realize selection of best viewpoints. The experimental results show that the algorithm has a faster convergence rate, and effectively reduces the number of evaluations. It can improve the quality and efficiency of the rendered 3D image.

Key words: 3D visualization, viewpoint optimization, Particle Swarm Optimization（PSO）, image information entropy