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视点选取为了提供给用户较好的观察位置,涉及到视点质量好坏的评估.提出了粒子群优化算法的三维可视化最佳视点选取方法.通过采用图像信息熵与图像边缘熵进行视点质量的评估,通过多目标智能优化方法选取视点.基本流程是由初始视点集开始,通过编码、粒子评价和粒子更新等操作寻找最佳视点,这是一个多次迭代的过程,直至找到满意的视点或者达到迭代最大代数.实验表明,该方法可行有效,能自动完成最佳视点的选取,有效地减少了人工试探选取次数.“,”The viewpoint selection is to automatically select one or more approximate optimal viewpoints in the viewpoints of multiple views,at the same time,it is related to the evaluation of the quality of the viewpoint.3D visualization best viewpoint selection method based on particle swarm optimization algorithm was proposed.The viewpoint quality was evaluated by using the image information entropy and the image edge entropy,and the viewpoint was selected by the multi-objective intelligent optimization method.The basic flow begins with the initial viewpoint set,finding the best viewpoint by means of coding,particle evaluation,and particle update,which is a process of multiple iterations until a satisfactory viewpoint is found or the iterations are maximized.Experiments show that the method is effective and can automatically select the best viewpoint,which can effectively reduce the number of artificial test selection.