| 期刊詳細資料 Journal detailed information |
| 作者(Author) | Tzu-Mao Li、Yu-Ting Wu、Yung-Yu Chuang |
| 是否為通作者(Is Corresponding Author?) | No |
| 篇名(Article title) | SURE-based Optimization for Adaptive Sampling and Reconstruction |
| 期刊名(Journal name) | ACM Transactions on Graphics |
| 國際期刊(International Journal) | SCIE |
| 中文摘要(Abstrct) | |
| ABSTRCT | We apply Stein's Unbiased Risk Estimator(SURE) to adaptive sampling and reconstruction to reduce noise in Monte Carlo rendering. SURE is a general unbiased estimator for mean squared error (MSE) in statistics. With SURE, we are able to estimate error for an arbitrary reconstruction kernel, enabling us to use more effective kernels rather than being restricted to the symmetric ones used in previous work. It also allows us to allocate more samples to areas with higher estimated MSE. Adaptive sampling and reconstruction can therefore be processed within an optimization framework. We also propose an efficient and memory-friendly approach to reduce the impact of noisy geometry features where there is depth of field or motion blur. Experiments show that our method produces images with less noise and crisper details than previous methods. |
| 中文關鍵字(Keyword) | |
| KEYWORD | |
| 卷期(Volume No) | Vol. 31 No. 6 |
| 頁數(Page number) | |
| 年份(Year) | 2012 |
| 語言(Language) | 英文 English |