Name
Abstract | ||
|---|---|---|
Efficient visualization of large volumetric data is a challenge for image processing community. In this paper, we present a novel volume rendering algorithm based on the concept of fractal. It consists of dividing the volumetric data set into sub-blocks, calculating the 3D fractal coefficients of each sub-block, projecting them to 2D image plane, and generating sub-images through 2D inverse fractal transform. The final rendered image is then obtained by simply summing the sub-images. Compared to the conventional ray casting technique, the proposed fractal volume rendering (FVR) method presents the advantage of reducing time complexity as well as memory complexity while maintaining good rendering quality. Moreover, the progressive refinement is supported owing to the iterative convergent process of sub-image generation |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660386 | ICASSP (2) |
Keywords | Field | DocType |
image processing,time complexity,image resolution,fractals,rendering quality,volumetric data visualization,rendering (computer graphics),progressive refinement,computational complexity,sub-image generation,2d image plane,ray casting technique,2d inverse fractal transform,3d fractal coefficients,transforms,memory complexity,fractal volume rendering algorithm,iterative convergent process,volume rendering,magnetic resonance imaging,casting,monte carlo methods,data visualization,computed tomography,ray casting | Computer vision,Volume rendering,3D rendering,Computer science,Fractal,Image processing,Ray casting,Artificial intelligence,Rendering (computer graphics),Fractal transform,Progressive refinement | Conference |
Volume | Issue | ISSN |
2 | null | 1520-6149 |
ISBN | Citations | PageRank |
1-4244-0469-X | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoliang Li | 1 | 28 | 7.12 |
| Hongxing Qin | 2 | 20 | 5.11 |
| Jie Yang | 3 | 1392 | 157.55 |
| Yuemin Zhu | 4 | 272 | 31.48 |