Abstract
The growing sizes of volumetric data sets pose a great challenge for interactive visualization. In this paper, we present a feature-preserving data reduction and focus+context visualization method based on transfer function driven, continuous voxel repositioning and resampling techniques. Rendering reduced data can enhance interactivity. Focus+context visualization can show details of selected features in context on display devices with limited resolution. Our method utilizes the input transfer function to assign importance values to regularly partitioned regions of the volume data. According to user interaction, it can then magnify regions corresponding to the features of interest while compressing the rest by deforming the 3D mesh. The level of data reduction achieved is significant enough to improve overall efficiency. By using continuous deformation, our method avoids the need to smooth the transition between low and high-resolution regions as often required by multiresolution methods. Furthermore, it is particularly attractive for focus+context visualization of multiple features. We demonstrate the effectiveness and efficiency of our method with several volume data sets from medical applications and scientific simulations.
| Original language | English (US) |
|---|---|
| Article number | 5416703 |
| Pages (from-to) | 171-181 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Visualization and Computer Graphics |
| Volume | 17 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 1 2011 |
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Keywords
- Data reduction
- focus+context visualization
- interactive visualization
- mesh deformation
- transfer functions
- volume rendering.
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design
Cite this
Feature-preserving volume data reduction and focus+context visualization. / Wang, Yu Shuen; Wang, Chaoli; Lee, Tong Yee; Ma, Kwan-Liu.
In: IEEE Transactions on Visualization and Computer Graphics, Vol. 17, No. 2, 5416703, 01.01.2011, p. 171-181.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Feature-preserving volume data reduction and focus+context visualization
AU - Wang, Yu Shuen
AU - Wang, Chaoli
AU - Lee, Tong Yee
AU - Ma, Kwan-Liu
PY - 2011/1/1
Y1 - 2011/1/1
N2 - The growing sizes of volumetric data sets pose a great challenge for interactive visualization. In this paper, we present a feature-preserving data reduction and focus+context visualization method based on transfer function driven, continuous voxel repositioning and resampling techniques. Rendering reduced data can enhance interactivity. Focus+context visualization can show details of selected features in context on display devices with limited resolution. Our method utilizes the input transfer function to assign importance values to regularly partitioned regions of the volume data. According to user interaction, it can then magnify regions corresponding to the features of interest while compressing the rest by deforming the 3D mesh. The level of data reduction achieved is significant enough to improve overall efficiency. By using continuous deformation, our method avoids the need to smooth the transition between low and high-resolution regions as often required by multiresolution methods. Furthermore, it is particularly attractive for focus+context visualization of multiple features. We demonstrate the effectiveness and efficiency of our method with several volume data sets from medical applications and scientific simulations.
AB - The growing sizes of volumetric data sets pose a great challenge for interactive visualization. In this paper, we present a feature-preserving data reduction and focus+context visualization method based on transfer function driven, continuous voxel repositioning and resampling techniques. Rendering reduced data can enhance interactivity. Focus+context visualization can show details of selected features in context on display devices with limited resolution. Our method utilizes the input transfer function to assign importance values to regularly partitioned regions of the volume data. According to user interaction, it can then magnify regions corresponding to the features of interest while compressing the rest by deforming the 3D mesh. The level of data reduction achieved is significant enough to improve overall efficiency. By using continuous deformation, our method avoids the need to smooth the transition between low and high-resolution regions as often required by multiresolution methods. Furthermore, it is particularly attractive for focus+context visualization of multiple features. We demonstrate the effectiveness and efficiency of our method with several volume data sets from medical applications and scientific simulations.
KW - Data reduction
KW - focus+context visualization
KW - interactive visualization
KW - mesh deformation
KW - transfer functions
KW - volume rendering.
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U2 - 10.1109/TVCG.2010.34
DO - 10.1109/TVCG.2010.34
M3 - Article
C2 - 21149874
AN - SCOPUS:78650168775
VL - 17
SP - 171
EP - 181
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 2
M1 - 5416703
ER -