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具有动态光照的始终高质量的实时逼真体绘制

Real-Time Realistic Volume Rendering of Consistently High Quality With Dynamic Illumination.

作者信息

Xu Chunxiao, Cheng Haojie, Chen Zhenxin, Wang Jiajun, Chen Yibo, Zhao Lingxiao

出版信息

IEEE Trans Vis Comput Graph. 2025 Sep;31(9):5288-5303. doi: 10.1109/TVCG.2024.3445339.

Abstract

Direct Volume Rendering (DVR) plays an important role in scientific data visualization. To generate photo-realistic DVR results, the physical light transport throughout the volume is simulated by applying the Monte Carlo-based volumetric path tracing (VPT) approach. For real-time applications, due to the time constraint for rendering each frame, only a limited number of samples shall be taken for the computation per pixel. This can result in a significant amount of noise in the rendering results. This paper describes our optimized VPT sampling algorithm and a novel denoising technique to generate consistently high-quality realistic DVR results in real time. We develop a new shading model that can reduce estimation variance to enhance the quality of DVR results. Additionally, a hybrid acceleration structure is created by integrating both octree and macrocell to improve sampling efficiency. This allows the acquisition of sufficiently more shading samples while maintaining the desired interactive frame rate. To further eliminate remaining noise and improve temporal stability of DVR results, we develop a novel spatiotemporal denoising framework. Our denoiser decouples the estimated radiance into high-detail low-noise and low-detail high-noise components. Different denoising algorithms are separately applied to these components to reduce noise without introducing blurring artifacts. Our DVR system can consistently offer high rendering quality and good temporal stability across DVR result frames in real time. During fast user interactions and with rapid alterations of the illumination condition, our rendering method can still provide good visual comfort and representation accuracy without visible latency.

摘要

直接体绘制(DVR)在科学数据可视化中起着重要作用。为了生成逼真的DVR结果,通过应用基于蒙特卡洛的体光线追踪(VPT)方法来模拟整个体数据中的物理光传输。对于实时应用,由于渲染每一帧的时间限制,每个像素的计算只能采用有限数量的样本。这可能会导致渲染结果中出现大量噪声。本文描述了我们优化的VPT采样算法和一种新颖的去噪技术,以实时生成始终高质量的逼真DVR结果。我们开发了一种新的着色模型,可以减少估计方差以提高DVR结果的质量。此外,通过集成八叉树和宏单元创建了一种混合加速结构,以提高采样效率。这使得在保持所需交互帧率的同时能够获取足够多的着色样本。为了进一步消除残留噪声并提高DVR结果的时间稳定性,我们开发了一种新颖的时空去噪框架。我们的去噪器将估计的辐射度解耦为高细节低噪声和低细节高噪声分量。不同的去噪算法分别应用于这些分量以减少噪声而不引入模糊伪影。我们的DVR系统能够实时在DVR结果帧之间始终提供高渲染质量和良好的时间稳定性。在快速用户交互期间以及照明条件快速变化时,我们的渲染方法仍然可以提供良好的视觉舒适度和表示精度,且无明显延迟。

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