We present an efficient raycasting algorithm for rendering Volumetric Depth Images (VDIs), and we show how it can be used in a remote visualization setting with VDIs generated and streamed from a remote server. VDIs are compact view-dependent volume representations that enable interactive visualization of large volumes at high frame rates by decoupling viewpoint changes from expensive rendering calculations. However, current rendering approaches for VDIs struggle with achieving interactive frame rates at high image resolutions. Here, we exploit the properties of perspective projection to simplify intersections of rays with the view-dependent frustums in a VDI and leverage spatial smoothness in the volume data to minimize memory accesses. Benchmarks show that responsive frame rates can be achieved close to the viewpoint of generation for HD display resolutions, providing high-fidelity approximate renderings of Gigabyte-sized volumes. We also propose a method to subsample the VDI for preview rendering, maintaining high frame rates even for large viewpoint deviations. We provide our implementation as an extension of an established open-source visualization library.
翻译:我们展示了一种高效的光谱算法,用于制作量子深度图像(VDIs),我们展示了如何在远程服务器生成和流出VDIs的远程可视化环境中使用它。VDIs是依靠视觉的缩放量缩放量缩放量缩放量的缩放量缩放量缩放量的缩放量表,通过将高成本的翻放量的视图转换速度与昂贵的翻放量的计算结果脱钩,使大宗量量的缩放量能够以高框架速率进行互动可视化。然而,目前VDIs为在以高图像分辨率实现交互式框架率而奋斗的方法。在这里,我们利用前景投影的特性来简化视光线的交叉点,在VDI中以视光为依附图的粗略度,并利用体积数据的空间平滑度来尽量减少内存存取量。基准显示响应性框架率可以接近HD显示分辨率的生成观点,提供高度的Gigabyte大小量的粗略度的缩放量。我们还提议一种方法,将VDI作为已建立的开源可视图书馆的扩展。</s>