Acceleration techniques for Rendering in general, and Ray-Casting in particular, have been the subject of much research in Computer Graphics. Most efforts have been focused on new data structures for efficient ray/scene traversal and intersection. In this paper, we propose an acceleration technique that approximates rendering and that is built around a new feature-based clustering approach. The technique starts preprocessing the scene by grouping elements according to their features using a set of channels based on an information theory-based approach. Then, at run-time, a rendering strategy uses that clustering information to reconstruct the final image, by deciding which areas could take advantage of the coherence in the features and thus, could be interpolated; and which areas require more involved calculations. This process starts with a low-resolution render that is iteratively refined up to the desired resolution by reusing previously computed pixels. Our experimental results show a significant speedup of an order of magnitude, depending on the complexity of the per-pixel calculations, the screen size of the objects, and the number of clusters. Rendering quality and speed directly depend on the number of clusters and the number of steps performed during the reconstruction procedure, and both can easily be set by the user. Our findings show that feature-based clustering can significantly impact rendering speed if samples are chosen to enable interpolation of smooth regions. Our technique, thus, accelerates a range of popular and costly techniques, ranging from texture mapping up to complex ambient occlusion, soft and hard shadow calculations, and it can even be used in conjunction with more traditional acceleration methods.

用于渲染的加速技术，尤其是光线投射，一直是计算机图形学中许多研究的主题。大多数努力都集中在用于有效光线/场景遍历和交叉的新数据结构上。在本文中，我们提出了一种近似渲染的加速技术，该技术围绕一种新的基于特征的聚类方法构建。该技术通过使用基于信息理论的方法的一组通道根据元素的特征对元素进行分组来开始对场景进行预处理。然后，在运行时，渲染策略使用该聚类信息来重建最终图像，通过决定哪些区域可以利用特征的相干性，从而可以进行插值；哪些领域需要更多的计算。此过程从低分辨率渲染开始，通过重复使用先前计算的像素，将其迭代细化到所需的分辨率。我们的实验结果显示了一个数量级的显着加速，这取决于每像素计算的复杂性、对象的屏幕大小和集群的数量。渲染质量和速度直接取决于在重建过程中执行的簇数和步骤数，并且两者都可以由用户轻松设置。我们的研究结果表明，如果选择样本来启用平滑区域的插值，则基于特征的聚类会显着影响渲染速度。因此，我们的技术加速了一系列流行且昂贵的技术，从纹理映射到复杂的环境遮挡、软和硬阴影计算，