Bruckner Stefan, Gröller Eduard
Institute of Computer Graphics and Algorithms, Vienna University of Technology, Austria.
IEEE Trans Vis Comput Graph. 2007 Nov-Dec;13(6):1344-51. doi: 10.1109/TVCG.2007.70555.
Volumetric data commonly has high depth complexity which makes it difficult to judge spatial relationships accurately. There are many different ways to enhance depth perception, such as shading, contours, and shadows. Artists and illustrators frequently employ halos for this purpose. In this technique, regions surrounding the edges of certain structures are darkened or brightened which makes it easier to judge occlusion. Based on this concept, we present a flexible method for enhancing and highlighting structures of interest using GPU-based direct volume rendering. Our approach uses an interactively defined halo transfer function to classify structures of interest based on data value, direction, and position. A feature-preserving spreading algorithm is applied to distribute seed values to neighboring locations, generating a controllably smooth field of halo intensities. These halo intensities are then mapped to colors and opacities using a halo profile function. Our method can be used to annotate features at interactive frame rates.
体数据通常具有很高的深度复杂度,这使得准确判断空间关系变得困难。有许多不同的方法来增强深度感知,例如阴影、轮廓和投影。艺术家和插画家经常为此使用光晕。在这种技术中,某些结构边缘周围的区域会变暗或变亮,这使得更容易判断遮挡情况。基于这一概念,我们提出了一种灵活的方法,使用基于GPU的直接体绘制来增强和突出感兴趣的结构。我们的方法使用交互式定义的光晕传递函数,根据数据值、方向和位置对感兴趣的结构进行分类。应用一种保留特征的扩散算法将种子值分布到相邻位置,生成一个可控的平滑光晕强度场。然后,使用光晕轮廓函数将这些光晕强度映射到颜色和不透明度。我们的方法可用于以交互式帧率注释特征。