›› 2011, Vol. 26 ›› Issue (2): 217-228.doi: 10.1007/s11390-011-1124-9

• Artificial Intelligence • Previous Articles     Next Articles

Visibility-Aware Direct Volume Rendering

Wai-Ho Mak1 (麦伟豪), Yingcai Wu (巫英才)2, Ming-Yuen Chan1 (陈明远), and Huamin Qu1 (屈华民), Member, IEEE   

  1. 1. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology Hong Kong, China;
    2. Department of Computer Science, The University of California, Davis, CA, U.S.A.
  • Received:2009-07-24 Revised:2010-11-28 Online:2011-03-05 Published:2011-03-05
  • About author:Wai-Ho Mak received the B.Eng. degree (first-class honors) in computer science and the M.Phil. degree in computer science and engineering both from the Hong Kong University of Science and Technology (HKUST) in 2007 and 2009 respectively. His research interests include scientific visualization and information visualization.
    Yingcai Wu is a post-doctoral researcher in the Department of Computer Science at The University of California, Davis. He obtained his B.Eng. degree (2004) in computer science and technology from South China University of Technology, China, and his Ph.D. (2009) degree in computer science and engineering from the HKUST. His research interests are in medical volume visualization and visual analytics.
    Ming-Yuen Chan received the B.Eng. degree (2003) in computer engineering from the University of Hong Kong and the M.Phil. (2006) and the Ph.D. degrees (2009) in computer science from the HKUST. His research interests include scientific visualization and medical imaging.
    Huamin Qu is an associate professor in the Department of Computer Science and Engineering at the HKUST. His main research interests are in visualization and computer graphics. He has conducted a wide range of research on scientific visualization, information visualization, real time graphics systems, virtual reality, and medical imaging. He received the B.S. degree in mathematics from Xi'an Jiaotong University, China, the M.S. and the Ph.D. degrees in computer science from the Stony Brook University, New York.
  • Supported by:

    The work is supported in part by Hong Kong RGC CERG under Grant No. 618705.

Direct volume rendering (DVR) is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images (DVRIs). However, end-users often feel that some risks are always associated with DVR because they do not know whether any important information is missing from the transparent regions of DVRIs. In this paper, we investigate how to semi-automatically generate a set of DVRIs and also an animation which can reveal information missed in the original DVRIs and meanwhile satisfy some image quality criteria such as coherence. A complete framework is developed to tackle various problems related to the generation and quality evaluation of visibility-aware DVRIs and animations. Our technique can reduce the risk of using direct volume rendering and thus boost the confidence of users in volume rendering systems.

[1] He T, Hong L, Kaufman A, Pfiter H. Generation of transfer functions with stochastic search techniques. In Proc. IEEE Visual. Conf., San Francisco, USA, Oct. 27-Nov. 1, 1996, pp.227-234.

[2] Kindlmann G, Durkin J W. Semi-automatic generation of transfer functions for direct volume rendering. In Proc. IEEE Symposium on Volume Visualization, Research Triangle Park, USA, Oct. 24, 1998, pp.79-86.

[3] Kniss J, McCormick P, McPherson A, Ahrens J, Painter J, Keahey A, Hansen C. Interactive texture-based volume rendering for large data sets. IEEE Computer Graphics and Applications, 2001, 21(4): 52-61.

[4] König A, Gröller E. Mastering transfer function specification by using volumepro technology. In Proc. Spring Conference on Computer Graphics, Budmerice, Slovakia, Apr. 25-28, 2001, pp.279-286.

[5] Tzeng F Y, Lum E B, Ma K L. A novel interface for higherdimensional classification of volume data. In Proc. IEEE Visual. Conf., Seattle, USA, Oct. 19-24, 2003, pp.505-512.

[6] Correa C, Ma K L. Visibility-driven transfer functions. In Proc. IEEE Pacific Visualization Symposium, Beijing, China, Apr. 20-23, 2009, pp.177-184.

[7] Mitchell M. An Introduction to Genetic Algorithms. Cambridge: MIT Press, MA, USA, 1996.

[8] House D, Bair A, Ware C. On the optimization of visualizations of complex phenomena. In Proc. IEEE Visualization Conf., Minneapolis, USA, Oct. 23-28, 2005, pp.87-94.

[9] Wu Y, Qu H. Interactive transfer function design based on editing direct volume rendered images. IEEE Trans. Visual. Comput. Graph., 2007, 13(5): 1027-1040.

[10] Sheikh H R, Sabir M F, Bovik A C. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. Image Processing, 2006, 15(11): 3441-3552.

[11] Sheikh H R, Bovik A C, Cormack L. No-reference quality assessment using natural scene statistics: JPEG2000. IEEE Transactions on Image Processing, 2005a, 14(11): 1918-1927.

[12] Gunawan I P, Ghanbari M. Reduced-reference video quality assessment using discriminative local harmonic strength with motion consideration. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(1): 71-83.

[13] Wang Z, Bovik A C. Modern Image Quality Assessment. Morgan and Claypool Publichers, 2006.

[14] Wang C, Garcia A, Shen H W. Interactive level-of-detail selection using image-based quality metric for large volume visualization. IEEE Transactions on Visualization and Computer Graphics, 2007, 13(1): 122-134.

[15] Wang C, Ma K L. A statistical approach to volume data quality assessment. IEEE Transactions on Visualization and Computer Graphics, 2008, 14(3): 590-602.

[16] Gröller M E, Purgathofer W. Coherence in computer graphics. Technical Report, TR-186-2-95-04, Institute of Computer Graphics and Algorithms, Vienna University of Technology, Austria, March 1995, Contact: technicalreport@cg.tuwien.ac.at.

[17] Lundstrom C, Ljung P, Ynnerman A. Local histograms for design of transfer functions in direct volume rendering. IEEE Trans. Visual. Comput. Graph., 2006, 12(6): 1570-1579.

[18] Weiskopf D, Engel K, Ertl T. Interactive clipping techniques for texture-based volume visualization and volume shading. IEEE Trans. Visual. Comput. Graph., 2003, 9(3): 298-312.

[19] Viola I, Kanitsar A, Gröller M E. Importance-driven feature enhancement in volume visualization. IEEE Trans. Visual. Comput. Graph., 2005, 11(4): 408-418.

[20] Krüger J, Schneider J,Westermann R. Clearview: An interactive context preserving hotspot visualization technique. IEEE Trans. Visual. Comput. Graph., 2006, 12(5): 941-948.

[21] Bruckner S, Grimm S, Kanitsar A, Gröller M E. Illustrative context-preserving exploration of volume data. IEEE Trans. Visual. Comput. Graph., 2006c, 12(6): 1559-1569.

[22] Rezk-Salama C, Kolb A. Opacity peeling for direct volume rendering. Computer Graphics Forum, 2006, 25(3): 597-606.
No related articles found!
Full text



[1] Wang Hui; Liu Dayou; Wang Yafei;. Sequential Back-Propagation[J]. , 1994, 9(3): 252 -260 .
[2] Peng Chenglian;. Combining Gprof and Event-Driven Monitoring for Analyzing Distributed Programs:A Rough View of NCSA Mosaic[J]. , 1996, 11(4): 427 -432 .
[3] Zhang Chenghong; Hu Yunfa; Shi Baile;. A Reasoning Mechanism for DeductiveObject-Oriented Databases[J]. , 1997, 12(4): 337 -345 .
[4] Jin-Woo Kim, Ju-Hum Kwon, Young-Gab Kim, Chee-Yang Song, Hyun-Seok Kim, and Doo-Kwon Baik. EAFoC: Enterprise Architecture Framework Based on Commonality[J]. , 2006, 21(6): 952 -964 .
[5] Pierre Bourque, Serge Oligny, Alain Abran, and Bertrand Fournier. Developing Project Duration Models in Software Engineering[J]. , 2007, 22(3): 348 -357 .
[6] Hai-Bin Zhang and Zhen-Hua Duan, Senior Member, CCF, IEEE. Symbolic Algorithmic Analysis of Rectangular Hybrid Systems[J]. , 2009, 24(3): 534 -543 .
[7] Bo Yu (于博) and Jian-Zhong Li (李建中), Member, CCF. Minimum-Time Aggregation Scheduling in Duty-Cycled Wireless Sensor Networks[J]. , 2011, 26(6): 962 -970 .
[8] Belal Al-Khateeb and Graham Kendall, Senior Member, IEEE. Effect of Look-Ahead Depth in Evolutionary Checkers[J]. , 2012, 27(5): 996 -1006 .
[9] Li-Feng He, Yu-Yan Chao, and Kenji Suzuki. An Algorithm for Connected-Component Labeling, Hole Labeling and Euler Number Computing[J]. , 2013, 28(3): 468 -478 .
[10] Hao Wang, Chao-Kun Wang, Ya-Jun Xu and Yuan-Chi Ning. Dominant Skyline Query Processing over Multiple Time Series[J]. , 2013, 28(4): 625 -635 .

ISSN 1000-9000(Print)

CN 11-2296/TP

Editorial Board
Author Guidelines
Journal of Computer Science and Technology
Institute of Computing Technology, Chinese Academy of Sciences
P.O. Box 2704, Beijing 100190 P.R. China
E-mail: jcst@ict.ac.cn
  Copyright ©2015 JCST, All Rights Reserved