体绘制中预计算梯度的下采样和存储

J. Díaz-García, P. Brunet, I. Navazo, Pere-Pau Vázquez
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引用次数: 0

摘要

在体数据集中计算梯度的方式既影响阴影的质量,也影响渲染算法中获得的性能。特别是,当在着色器代码中通过访问邻近位置实时评估梯度时,多分辨率表示中的粗数据集的可视化会受到影响。我们提出了一种预计算梯度的下采样滤波器,它提供了更好地匹配原始梯度的改进梯度,从而使上述伪影消失。其次,为了解决存储问题,我们提出了一种有效存储梯度方向的方法,该方法能够在3字节的空间内最小化所有可表示向量之间的最小角度。
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Downsampling and Storage of Pre-Computed Gradients for Volume Rendering
The way in which gradients are computed in volume data-sets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. We propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes.
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