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| Content Provider | Springer Nature Link |
|---|---|
| Author | Fang, MeiE Lu, Jia Peng, QunSheng |
| Copyright Year | 2014 |
| Abstract | The existing methods for visualizing volumetric data are mostly based on piecewise linear models. And all kinds of analysis based on them have to be substituted by coarse interpolations. So both accuracy and reliability of the traditional framework for visualization and analysis of volumetric data are far from our needs of digging information implied in volumetric data fields. In this paper, we propose a novel framework based on a C $^{2}$-continuous seven-directional box spline, under which reconstruction is of high accuracy and differential computations relative to analysis based on the reconstruction model are accurate. We introduce a polynomial differential operator to improve the reconstruction accuracy. In order to settle the difficulty of evaluating upon the seven-directional box spline, we convert it into Bézier form and propose effective theories and algorithms of extracting iso-surfaces, critical points and curvatures. Plentiful of examples are also given in this paper to illustrate that the novel framework is suitable for analysis, the improved reconstruction method has high accuracy, and our algorithms are fast and stable. |
| Starting Page | 1 |
| Ending Page | 14 |
| Page Count | 14 |
| File Format | |
| ISSN | 1674733X |
| Journal | Science in China Series : Information Sciences |
| Volume Number | 57 |
| Issue Number | 6 |
| e-ISSN | 18691919 |
| Language | English |
| Publisher | Science China Press |
| Publisher Date | 2014-01-08 |
| Publisher Place | Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | volumetric data visualization and analysis seven-directional box spline iso-surface critical points curvature Information Systems and Communication Service |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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