基于信息熵的并行自适应体绘制算法

Huawei Wang, Yi Cao, Li Xiao, Guoqing Wu
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引用次数: 1

摘要

本文提出了一种基于信息熵的并行自适应光线投射体绘制算法,该算法利用信息熵来度量数据场中物理特征的分布,从而指导有效的数据采样。该算法采用逐块自适应,根据数据块的信息熵分配不同的采样率,在每个数据块内采用均匀采样。针对每条射线上的非均匀采样点,设计了一种组合方法。实验表明,与均匀渲染算法相比,本文提出的自适应渲染算法在分布式内存环境下的渲染加速比可达1.4~2.1。
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A Parallel Adaptive Volume Rendering Algorithm Based on Information Entropy
A parallel adaptive ray-casting volume rendering algorithm based on information entropy is presented in this paper, where information entropy is introduced to measure the distribution of physical features in a data field and accordingly guide an effective data sampling. The algorithm adopts a patch-wise adaptation: Different sampling rates are assigned to the data patches according to their information entropies while uniform sampling is employed within each data patch. A composing method is designed subsequently for non-uniform sampling points on each ray. The experiments show that compared with the uniform rendering algorithm, the presented adaptive rendering algorithm can achieve a rendering speedup ratio of 1.4~2.1 in a distributed-memory environment.
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