基于Woodcock Tracking的快速蒙特卡罗直接体绘制方法

doi:10.16182/j.issn1004731x.joss.201705026

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (5): 1125-1131.doi: 10.16182/j.issn1004731x.joss.201705026

基于Woodcock Tracking的快速蒙特卡罗直接体绘制方法

周守东

安徽工业经济职业技术学院,安徽合肥 230051

收稿日期:2016-05-04 修回日期:2016-08-09 出版日期:2017-05-08 发布日期:2020-06-03
作者简介:周守东(1981-),男,安徽铜陵,硕士,讲师,研究方向为图形学,虚拟仿真应用,计算机应用技术。
基金资助:
安徽省重点自然科学研究项目(KJ2015A381), 安徽省高校优秀青年人才支持计划(gxyq2017177)

Woodcock Tracking Based Fast Monte Carlo Direct Volume Rendering Method

Zhou Shoudong

Anhui Technical College of Industray and Economy, Hefei 230051, China

Received:2016-05-04 Revised:2016-08-09 Online:2017-05-08 Published:2020-06-03

摘要/Abstract

摘要： Woodcock-Tracking采样算法是一种常用的光线采样方法,对于优化蒙特卡罗直接体绘制方法具有重要的作用。目前该方法没有考虑体数据不同区域颜色的变化,导致颜色变化剧烈的区域可能只有少量采样点,影响体数据的真实性。引入信息熵表征体数据不同区域变化的剧烈程度,基于信息熵发展了自适应Woodcock-Tracking方法,使得变化剧烈区域获取更多采样点;运用加权颜色合成算法,实现无偏渲染。通过对头颅、背包和骨骼三个模型的对比测试,结果均表明该方法对渲染质量有明显改善。

关键词: 直接体绘制, 全局光照, 蒙特卡罗光线跟踪, 信息熵, Woodcock-Tracking

Abstract: Woodcock-Tracking sampling algorithm is a frequently applied ray sampling method, which plays an important role in optimizing the Monte Carlo direct volume rendering method. However, without considering the volume of color's variation in different region by using this method, the situation that region with great color's variation may only get a few samples was caused and the authenticity of volume data would be affected. Entropy to indicate color's variation in volume was introduced, an entropy based adaptive Woodcock-Tracking method was developed, which could sample more points in region with higher color's variation. To overcome biases caused by adaptive Woodcock-Tracking method, weighted color evaluation method was used, so that the final render result image was unbiased. Through the contrast test on the three models of head, backpack and skeleton, the result demonstrates the presented method is superior to the current method in the aspect of improving the rendering quality obviously.

Key words: direct volume rendering, global illumination, Monte Carlo tay tracing, entropy, woodcock-tracking

中图分类号:

TP391.41

周守东. 基于Woodcock Tracking的快速蒙特卡罗直接体绘制方法[J]. 系统仿真学报, 2017, 29(5): 1125-1131.

Zhou Shoudong. Woodcock Tracking Based Fast Monte Carlo Direct Volume Rendering Method[J]. Journal of System Simulation, 2017, 29(5): 1125-1131.

参考文献

[1] Charles D Hansen, Chris R Johnson.The Visualization Handbook [M]. Holland: ELSEVIER Academic Press, 2004.
[2] Marc Leovy.Efficient ray tracing of volume data[J]. ACM Transactions on Graphics (S0730-0301), 1990, 9(3): 245-261.
[3] Levoy M.Ahybrid Ray Tracer for Rendering Polygon and Volume Data[J]. IEEE Computer Graphics and Applications (S0272-1716), 1990, 10(2): 33-40.
[4] B Csebfalvi, L Szirmay-Kalos.Monte Carlo Volume Rendering[C]// Proceedings of the IEEE Visualization Conference, VIS 2003, Seattle, WA, United States. USA: IEEE, 2003.
[5] Matthias Raab, Daniel Seibert, Alexander Keller.Unbiased global illumination with participating media[C]// Monte Carlo and Quasi-Monte Carlo Methods 2006. Berlin Heidelberg, Germany: Springer-Verlag, 2008: 591-605.
[6] Eric Veach, Leonidas J Guibas.Optimally combining sampling techniques for Monte Carlo rendering[C]// Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques. Vancouver, Canada : The University of British Columbia , 1995: 419-428.
[7] Peter S Shirley.Physically based lighting calculations for computer graphics [D]. USA: University of Illinois, 1991.
[8] Peter Shirley.Discrepancy as a quality measure for sample distributions[C]// Proceedings of Eurographics' 91. Vienna, Austria: North-Holland, 1991: 183-194.
[9] Eric Lafortune.Mathematical models and Monte Carlo algorithms for physically based rendering [D]. Belgiam: Katholieke Universiteit Leuven, 1996.
[10] Mitchell D P.Generating antialiased images at low sampling densities[C]// SIGGRAPH'87: Conference on Computer Graphics and Interactive Techniques.Anaheim, California, USA : ACM Press, 1987: 65-72.
[11] Mark E Lee, Richard A Redner, Samuel P Uselton.Statistically optimized sampling for distributed ray tracing [C]// SIGGRAPH'85: Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques. New York, N Y, USA: ACM Press, 1985: 61-68.
[12] Wolf W, Ozer B, Lv T.Smart cameras as embedded systems[J]. Computer (S0018-9162), 2002, 35(9): 48-53.
[13] Kirk D, Arvo J.Unbiased Variance Reduction for Global Illumination[M]. Photorealistic Rendering in Computer Graphics. , Germany Springer, Berlin Heidelberg, 1994: 45-51.
[14] Rigau J, Feixas M, Sbert M.Entropy-based Adaptive Sampling[C]//Proceedings of Graphics Interface 2003. Halifax, Nova Scotia, Canada: Canadian Human- Computer Communications Society and A K Peters Ltd. 2003: 159-166.
[15] Kajiya J T.The Rendering Equation [C]// SIGGRAPH '86: Proceedings of the 13th Annual Conference on Computer Graphics and Interactive Techniques. New York, N Y, USA: ACM Press, 1986: 143-150.
[16] Veach E, Guibas L.Bidirectional Estimators for Light Transport[M]. Photorealistic Rendering Techniques. Berlin Heidelberg, Germany: Springer, 1995: 145-167.
[17] Veach E, Guibas L J.Metropolis light transport[C]// SIGGRAPH '97(1997). USA: ACM, 1997: 65-76.
[18] Parker S G, Boulos S, Bigler J, et al.RTSL: a Ray Tracing Shading Language[C]// Interactive Ray Tracing, 2007. RT '07. IEEE Symposium on. IEEE Xplore, IEEE DC, USA: Computer Society Washington, 2007: 149-160.
[19] Cover T M, Thomas J A.Elements of information theory[M]. New York, USA: Wiley-Interscience, 1991: 371-395.
[20] Purchase H C, Andrienko N, Jankun-Kelly T J, et al. Theoretical foundations of information visualization[M]// Information Visualization: Human-centered Issues and Perspectives. Kerren A, Stasko J T, Fekete J D, et al. Eds. Berlin/ Heidelberg, Germany: Springer-Verlag, 2008: 46-64.
[21] M Feixas, E del Acebo, P Bekaert, et al. An information theory framework for the analysis of scene complexity[J]. Computer Graphics Forum (S0167-7055), 1999, 18(3): 95-106.
[22] J Rigau, M Feixas, M Sbert.Shape complexity based on mutual information[C]// Proc. IEEE Shape Modeling and Applications, 2005. USA: IEEE, 2005.
[23] S Gumhold.Maximum entropy light source placement[C]// Proc. IEEE Visualization. USA: IEEE, 2002: 275-282.
[24] S Takahashi, Y Takeshima.A feature-driven approach to locating optimal viewpoints for volume visualization[C]// Proc. IEEE Visualization. USA: IEEE, 2005: 495-502.
[25] Xu L, Lee T Y, Shen H W.An information-theoretic framework for flow visualization[J]. IEEE Transactions on Visualization & Computer Graphics (S1077-2626), 2010, 16(6):1216-1224.
[26] Y Chen, J Cohen, J Krolik.Similarity-guided streamline placement with error evaluation[J]. IEEE Transactions on Visualization and Computer Graphics (S1077-2626), 2007, 13(6): 1448-1455.
[27] Verma V, Kao D, Pang A.A Flow-guided Streamline Seeding Strategy[C]// Proceedings of The Conference on Visualization, Salt Lake City, UT, USA. USA: IEEE, 2000: 163-170.
[28] Kroes T, Post F H, Botha C P.Correction: Exposure Render: An Interactive Photo-Realistic Volume Rendering Framework[J]. Plos One (S2333-9721), 2013, 7(7): e38586.
[29] Lum E B, Wilson B, Ma K-l.High-quality lighting and efficient pre-integration for volume rendering[C]// Proceedings Joint Eurographics-IEEE TVCG Symposium on Visualization 2004 (VisSym'04). USA: IEEE, 2004: 25-34.

基于Woodcock Tracking的快速蒙特卡罗直接体绘制方法

Woodcock Tracking Based Fast Monte Carlo Direct Volume Rendering Method

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