We present a hybrid multi-volume rendering approach based on a novel Residency Octree that combines the advantages of out-of-core volume rendering using page tables with those of standard octrees. Octree approaches work by performing hierarchical tree traversal. However, in octree volume rendering, tree traversal and the selection of data resolution are intrinsically coupled. This makes fine-grained empty-space skipping costly. Page tables, on the other hand, allow access to any cached brick from any resolution. However, they do not offer a clear and efficient strategy for substituting missing high-resolution data with lower-resolution data. We enable flexible mixed-resolution out-of-core multi-volume rendering by decoupling the cache residency of multi-resolution data from a resolution-independent spatial subdivision determined by the tree. Instead of one-to-one node-to-brick correspondences, each residency octree node is mapped to a set of bricks from different resolution levels. This makes it possible to efficiently and adaptively choose and mix resolutions, adapt sampling rates, and compensate for cache misses. At the same time, residency octrees support fine-grained empty-space skipping, independent of the data subdivision used for caching. Finally, to facilitate collaboration and outreach, and to eliminate local data storage, our implementation is a web-based, pure client-side renderer using WebGPU and WebAssembly. Our method is faster than prior approaches and efficient for many data channels with a flexible and adaptive choice of data resolution.

翻译：我们提出了一种基于新型居住八叉树的混合多体绘制方法，该方法结合了基于页表的外核体绘制与标准八叉树的优势。八叉树方法通过执行层次化树遍历实现绘制，但其树遍历与数据分辨率选择存在内在耦合，导致细粒度空白跳跃成本高昂。相比之下，页表允许访问任意分辨率的缓存块，但缺乏以低分辨率数据替代缺失高分辨率数据的明确高效策略。我们通过解耦多分辨率数据的缓存驻留性与由树确定的与分辨率无关的空间细分，实现了灵活的多分辨率外核多体绘制。每个居住八叉树节点不再遵循一对一节点-块映射，而是映射到来自不同分辨率层次的多个数据块，从而能够高效自适应地选择与混合分辨率、调整采样率并补偿缓存缺失。同时，居住八叉树支持与缓存数据细分无关的细粒度空白跳跃。为促进协作与推广并消除本地数据存储需求，我们的实现基于WebGPU和WebAssembly的纯客户端Web渲染器。实验表明，该方法在多个数据通道下比现有方法更快，并能灵活自适应地选择数据分辨率。