视点相关光线投射算法在三维云可视化方面的应用

Ray Casting Algorithm Based on Viewpoint Correlation for 3D Cloud Visualization

摘要:

针对绘制海量云数据时传统光线投射算法计算量大、绘制缓慢等问题,提出了一种基于视点相关光线投射算法的三维云可视化方法。该方法首先采用基于多分辨率方法的数据预处理策略,然后采用基于视点相关系数的自适应采样频率计算方法确定重采样点的位置,并利用三阶段插值算法计算重采样点的值,最后采用基于块重要性加权香农熵的二维传输函数完成颜色值和不透明度的映射关系,从而实现图像的合成。实验结果表明,该方法计算复杂度低、执行效率高,与现有的光线投射算法相比,不仅图像的重构质量得到了提高,绘制时间也减少了约30%。

Abstract:

Aiming at the problems of large amount of computation and slow drawing presented in traditional ray casting algorithm when drawing massive cloud data, a three-dimensional cloud visualization method is proposed based on viewpoint-related ray casting algorithm. Firstly, it adopts the data preprocessing strategy based on multi-resolution method, then adopts the adaptive sampling frequency calculation method based on the viewpoint correlation coefficient to determine the position of the resampling point, and uses the three-stage interpolation algorithm to calculate the value of the resampling point. Finally the two-dimensional transfer function based on the block importance weighting Shannon entropy is used to complete the mapping relationship between color value and opacity, thereby realizing image synthesis. The experimental results show that the method realizes low computational complexity and high execution efficiency, and compared with the existing ray casting algorithms, its not only the image reconstruction quality is improved, but also the drawing time is reduced by about 30%.