用于可视化体数据的可探索图像

Anna Tikhonova, Carlos D. Correa, K. Ma
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引用次数: 54

摘要

我们提出了一种技术,可以自动将相同3D数据集的少量单视图体渲染图像转换为该数据集的紧凑表示。这种表示是一种多层图像,或可探索图像,它允许在不访问原始数据的情况下对传递函数空间中的体数据进行交互式探索。我们通过自动提取合成图像中的图层来实现这一点。然后可以用不同的方式重新组合图层来模拟单个特征的不透明度变化和重新上色。我们的研究结果表明,当体数据太大而无法进行交互式探索时,可探索图像特别有用,由于底层网格结构或期望的阴影效果,渲染时间太长,或者原始体数据不可用时,可探索图像特别有用。可浏览图像可以提供基于图像的实时交互,作为一种预览机制,用于远程可视化或在低端硬件、移动设备或Web浏览器中可视化大量数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Explorable images for visualizing volume data
We present a technique which automatically converts a small number of single-view volume rendered images of the same 3D data set into a compact representation of that data set. This representation is a multi-layered image, or an explorable image, which enables interactive exploration of volume data in transfer function space without accessing the original data. We achieve this by automatically extracting layers depicted in composited images. The layers can then be recombined in different ways to simulate opacity changes and recoloring of individual features. Our results demonstrate that explorable images are especially useful when the volume data is too large for interactive exploration, takes too long to render due to the underlying mesh structure or desired shading effect, or if the original volume data is not available. Explorable images can offer real-time image-based interaction as a preview mechanism for remote visualization or visualization of large volume data on low-end hardware, within a mobile device, or a Web browser.
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