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Perception-Based Transparency Optimization for Direct Volume Rendering

机译:直接体积渲染的基于感知的透明度优化

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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
机译:直接体积渲染图像的半透明性质可用于描述体积中的分层结构。但是,要获得具有清晰可见层的半透明结果很困难,并且可能需要对不透明度和其他渲染参数进行繁琐的调整。此外,层的视觉质量还取决于各种感知因素。在本文中,我们提出了一种自动校正方法,用于增强直接体积渲染图像中半透明层的感知质量。我们引入了一套基于心理原理的新措施,以评估渲染图像中透明结构的感知质量。通过在自适应和直观的用户交互过程中优化渲染参数,可以提高图像质量,从而可以满足特定的用户要求。在各种数据集上的实验结果证明了我们方法的有效性和鲁棒性

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