A Perceptual Framework for Comparisons of Direct Volume Rendered Images

  • Hon-Cheng Wong
  • Huamin Qu
  • Un-Hong Wong
  • Zesheng Tang
  • Klaus Mueller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)


Direct volume rendering (DVR) has been widely used by physicians, scientists, and engineers in many applications. There are various DVR algorithms and the images generated by these algorithms are somewhat different. Because these direct volume rendered images will be perceived by human beings, it is important to evaluate their quality based on human perception. One of the key perceptual factors is that whether and how the visible differences between two images will be observed by users. In this paper we propose a perceptual framework, which is based on the Visible Differences Predictor (VDP), for comparing the direct volume rendered images generated with different algorithms or the same algorithm with different specifications such as shading method, gradient estimation scheme, and sampling rate. Our framework consists of a volume rendering engine and a VDP component. The experimental results on some real volume data show that the visible differences between two direct volume rendered images can be measured quantitatively with our framework. Our method can help users choose suitable DVR algorithms and specifications for their applications from a perceptual perspective and steer the visualization process.


Human Visual System Graphic Hardware Global Illumination Direct Volume Volume Visualization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hon-Cheng Wong
    • 1
  • Huamin Qu
    • 2
  • Un-Hong Wong
    • 1
  • Zesheng Tang
    • 1
  • Klaus Mueller
    • 3
  1. 1.Faculty of Information TechnologyMacau University of Science and TechnologyMacaoChina
  2. 2.Department of Computer Science and EngineeringHong Kong University of Science and TechnologyHong KongChina
  3. 3.Department of Computer ScienceStony Brook UniversityStony BrookUSA

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