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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.16684 |
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| _version_ | 1866908601913704448 |
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| author | Zhao, Devin Wenger, Rephael |
| author_facet | Zhao, Devin Wenger, Rephael |
| contents | Let $f: \mathbb{R}^3 \rightarrow \mathbb{R}$ be a scalar field. An isosurface is a piecewise linear approximation of a level set $f^{-1}(σ)$ for some $σ\in \mathbb{R}$ built from some regular grid sampling of $f$. Isosurfaces constructed from scanned data such as CT scans or MRIs often contain extremely small components that distract from the visualization and do not form part of any geometric model produced from the data. Simple prefiltering of the data can remove such small components while having no effect on the large components that form the body of the visualization. We present experimental results on such filtering. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_16684 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Filtering of Small Components for Isosurface Generation Zhao, Devin Wenger, Rephael Graphics Computer Vision and Pattern Recognition I.3 Let $f: \mathbb{R}^3 \rightarrow \mathbb{R}$ be a scalar field. An isosurface is a piecewise linear approximation of a level set $f^{-1}(σ)$ for some $σ\in \mathbb{R}$ built from some regular grid sampling of $f$. Isosurfaces constructed from scanned data such as CT scans or MRIs often contain extremely small components that distract from the visualization and do not form part of any geometric model produced from the data. Simple prefiltering of the data can remove such small components while having no effect on the large components that form the body of the visualization. We present experimental results on such filtering. |
| title | Filtering of Small Components for Isosurface Generation |
| topic | Graphics Computer Vision and Pattern Recognition I.3 |
| url | https://arxiv.org/abs/2510.16684 |