2013
DOI: 10.1007/s11432-013-4834-5
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An optimized texture-by-numbers synthesis method and its visual applications

Abstract: The framework of texture-by-numbers (TBN) synthesizes images of global-varying patterns with intuitive user control. Previous TBN synthesis methods have difficulties in achieving high-quality synthesis results and efficiency simultaneously. This paper proposes a fast TBN synthesis method based on texture optimization, which uses global optimization to solve the controllable non-homogeneous texture synthesis problem. Our algorithm produces high quality synthesis results by combining texture optimization into TB… Show more

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(1 citation statement)
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“…This study uses Laplacian image-based geometry texture synthesis [33] and optimized texture-by-numbers synthesis method [34] as baselines for comparison. The spatio-temporal performance of the suggested method and the baselines are compared using the synthesis of grass texture sam-ples as an example, and the results are presented in Tables 1 and 2.…”
Section: πœ‘ = |𝑆 βˆ’ 𝑆 |mentioning
confidence: 99%
“…This study uses Laplacian image-based geometry texture synthesis [33] and optimized texture-by-numbers synthesis method [34] as baselines for comparison. The spatio-temporal performance of the suggested method and the baselines are compared using the synthesis of grass texture sam-ples as an example, and the results are presented in Tables 1 and 2.…”
Section: πœ‘ = |𝑆 βˆ’ 𝑆 |mentioning
confidence: 99%