Component-Based Adaptive Sampling

K. Debattista, A. Chalmers
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引用次数: 6

Abstract

High-fidelity renderings of virtual environments is a notoriously computationally expensive task. One commonly used method to alleviate the costs is to adaptively sample the rendered images identifying the required number of samples according to the variance of the area thus reducing aliasing and concurrently reducing the total number of rays shot. When using ray tracing algorithms, the traditional method is to shoot a number of rays and depending on the difference between the radiance of the samples further rays may be shot. This approach fails to take into account that different components of a material reflecting light may exhibit more coherence than others. With this in mind we present a component-based adaptive sampling algorithm that renders components individually and adaptively samples at the component level, finally composting the result to produce a full solution. Results demonstrate a significant improvement in performance without any perceptual loss in quality.
基于组件的自适应采样
众所周知,虚拟环境的高保真渲染是一项计算成本高昂的任务。一种常用的降低成本的方法是对渲染图像进行自适应采样,根据面积的变化来识别所需的采样数量,从而减少混叠,同时减少拍摄的射线总数。在使用光线追踪算法时,传统的方法是拍摄一些光线,根据样品的亮度差异,可以拍摄更多的光线。这种方法没有考虑到材料反射光的不同成分可能比其他成分表现出更多的相干性。考虑到这一点,我们提出了一种基于组件的自适应采样算法,该算法在组件级别上呈现组件单独和自适应采样,最后将结果堆肥以产生完整的解决方案。结果表明,在没有任何感知质量损失的情况下,性能有了显著提高。
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