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In computed tomography, the approximation quality of a scan of a physicalobject is typically limited by the acquisition modalities, especially thehardware including X-ray detectors. To improve upon this, we experiment with athree-dimensional subdivision scheme to increase the resolution of thereconstructed voxel data. Subdivision schemes are often used to refinetwo-dimensional manifolds (mostly meshes) leading to smoother surfaces. In thiswork, we apply a refinement scheme to three-dimensional data first, and onlythen, start the surface extraction process. Thus, the main subject of this worklies not on subdivision surfaces, but rather on subdivision volumes. In thevolumetric case, each subdivision iteration consumes eight times more storagespace than the previous one. Hence, we restrict ourselves to a singlesubdivision iteration. We evaluate the quality of the produced subdivisionvolumes using synthetic and industrial data. Furthermore, we considermanufacturing errors in the original and in the subdivision volumes, extracttheir surfaces, and compare the resulting meshes in critical regions.Observations show that our specific choice of a subdivision scheme producessmoothly interpolated data while also preserving edges.

Towards smoother surfaces by applying subdivision to voxel data