Perception-Based Transparency Optimization
for Direct Volume Rendering

IEEE Visualization 2009 Honorable Mention Award
IEEE Transactions on Visualization and Computer Graphics (IEEE Visualization 2009)

Ming-Yuen Chan2     Yingcai Wu1     Wai-Ho Mak2     Wei Chen3     Huamin Qu2
1Microsoft Research Asia      2Hong Kong University of Science and Technology       2Zhejiang University

Teaser Image

Experiment on the effect of color on transparency perception using Neghip dataset. The outer layer structures in pink are assigned with different saturation values. From left to right: 100%, 75%, 50%, and 25%. The results show different transparency effects.

Abstract

The semi-transparent nature of direct volume rendered images is useful to depict layered structures in a volume. However, obtaining a semi-transparent result with the layers clearly revealed is difficult and may involve tedious adjustment on opacity and other rendering parameters. Furthermore, the visual quality of layers also depends on various perceptual factors. In this paper, we propose an auto-correction method for enhancing the perceived quality of the semi-transparent layers in direct volume rendered images. We introduce a suite of new measures based on psychological principles to evaluate the perceptual quality of transparent structures in the rendered images. By optimizing rendering parameters within an adaptive and intuitive user interaction process, the quality of the images is enhanced such that specific user requirements can be met. Experimental results on various datasets demonstrate the effectiveness and robustness of our method.

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BibTeX

@article {YWu2009b,
author = {Ming-Yuen Chan and Yingcai Wu and Wai-Ho Mak and Wei Chen and Huamin Qu},
title = {Perception-Based Transparency Optimization for Direct Volume Rendering} ,
journal = {IEEE Transactions on Visualization and Computer Graphics},
year = {2009},
volume = {15},
number = {6},
pages = {1283--1290 }
}