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High quality solid texture synthesis using position and index histogram matching

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Abstract

The synthesis quality is one of the most important aspects in solid texture synthesis algorithms. In recent years several methods are proposed to generate high quality solid textures. However, these existing methods often suffer from the synthesis artifacts such as blurring, missing texture structures, introducing aberrant voxel colors, and so on. In this paper, we introduce a novel algorithm for synthesizing high quality solid textures from 2D exemplars. We first analyze the relevant factors for further improvements of the synthesis quality, and then adopt an optimization framework with the k-coherence search and the discrete solver for solid texture synthesis. The texture optimization approach is integrated with two new kinds of histogram matching methods, position and index histogram matching, which effectively cause the global statistics of the synthesized solid textures to match those of the exemplars. Experimental results show that our algorithm outperforms or at least is comparable to the previous solid texture synthesis algorithms in terms of the synthesis quality.

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Authors and Affiliations

  1. School of Software, Tsinghua University, Beijing, 100084, China

    Jiating Chen & Bin Wang

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Jiating Chen

  3. Key Laboratory for Information System Security, Ministry of Education, Beijing, 100084, China

    Jiating Chen & Bin Wang

  4. Tsinghua National Laboratory for Information Science and Technology, Beijing, 100084, China

    Jiating Chen & Bin Wang

Authors
  1. Jiating Chen
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  2. Bin Wang
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Correspondence to Jiating Chen.

Additional information

This paper is based on Solid Texture Synthesis using Position Histogram Matching, by Jiating Chen and Bin Wang, which appeared in the Proceedings of IEEE CAD/Graphics 2009.

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Chen, J., Wang, B. High quality solid texture synthesis using position and index histogram matching. Vis Comput 26, 253–262 (2010). https://doi.org/10.1007/s00371-009-0408-3

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  • DOI: https://doi.org/10.1007/s00371-009-0408-3