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Title:
Parallel adaptive sampling and reconstruction using multi-scale and directional analysis
Author: Liu, Xiao Dan (1) ; Zheng, Chang Wen (1)
Issued Date: 2013
Keyword: Contourlet ; Adaptive sampling ; Anisotropic filter ; Multi-scale analysis
Corresponding Author: Liu, X.D.(lxdfigo@163.com)
Publish Place: Springer Verlag
Indexed Type: SCI ; EI
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
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.
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.
Language: 英语
Citation statistics:
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16555
Appears in Collections:软件所图书馆_会议论文

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