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| Parallel adaptive sampling and reconstruction using multi-scale and directional analysis | |
| Liu, Xiao Dan (1); Zheng, Chang Wen (1); Liu, X.D.(lxdfigo@163.com) | |
| 2013 | |
| Pages | 501-511 |
| Indexed Type | SCI ; EI |
| Publish Place | Springer Verlag |
| ISSN | 1782789 |
| Department | (1) National Key Laboratory of Integrated Information System Technology, Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Graduate University of Chinese Academy of Sciences, Beijing, China |
| English Abstract | We propose a novel parallel image space adaptive rendering approach. Contourlet transform which includes Laplacian pyramid and directional filter banks is modified for multi-scale and directional analysis in our algorithm. In sampling stage, the image space is coarsely sampled first. The sampled image is analyzed into coarse and difference values in multi-scale using Laplacian pyramid transform. Based on the analysis, a heuristic method is proposed to repeatedly distribute adaptive Monte Carlo samples. In reconstruction stage, the final image is reconstructed by filtering each pixel using our anisotropic per-pixel filter. The filter size depends on the variance and attenuation values. The filter's anisotropic property is computed by the directional filter banks. Compared to the state-of-the-art image space adaptive rendering methods, the results rendered by our algorithm show improvement in both visual image quality and numerical error while using sparse samples. © 2013 Springer-Verlag Berlin Heidelberg.; We propose a novel parallel image space adaptive rendering approach. Contourlet transform which includes Laplacian pyramid and directional filter banks is modified for multi-scale and directional analysis in our algorithm. In sampling stage, the image space is coarsely sampled first. The sampled image is analyzed into coarse and difference values in multi-scale using Laplacian pyramid transform. Based on the analysis, a heuristic method is proposed to repeatedly distribute adaptive Monte Carlo samples. In reconstruction stage, the final image is reconstructed by filtering each pixel using our anisotropic per-pixel filter. The filter size depends on the variance and attenuation values. The filter's anisotropic property is computed by the directional filter banks. Compared to the state-of-the-art image space adaptive rendering methods, the results rendered by our algorithm show improvement in both visual image quality and numerical error while using sparse samples. © 2013 Springer-Verlag Berlin Heidelberg. |
| Keyword | Contourlet Adaptive Sampling Anisotropic Filter Multi-scale Analysis |
| Language | 英语 |
| WOS ID | WOS:000319478400005 |
| Citation statistics | |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16555 |
| Collection | 中国科学院软件研究所 |
| Corresponding Author | Liu, X.D.(lxdfigo@163.com) |
| Recommended Citation GB/T 7714 | Liu, Xiao Dan ,Zheng, Chang Wen ,Liu, X.D.. Parallel adaptive sampling and reconstruction using multi-scale and directional analysis[C]. Springer Verlag,2013:501-511. |
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