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Parallel adaptive sampling and reconstruction using multi-scale and directional analysis

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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.

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Authors and Affiliations

  1. National Key Laboratory of Integrated Information System Technology, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Xiao Dan Liu & Chang Wen Zheng

  2. Graduate University of Chinese Academy of Sciences, Beijing, China

    Xiao Dan Liu

Authors
  1. Xiao Dan Liu
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  2. Chang Wen Zheng
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Correspondence to Xiao Dan Liu.

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Liu, X.D., Zheng, C.W. Parallel adaptive sampling and reconstruction using multi-scale and directional analysis. Vis Comput 29, 501–511 (2013). https://doi.org/10.1007/s00371-013-0814-4

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  • DOI: https://doi.org/10.1007/s00371-013-0814-4

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