Computational Visual Media (Jun 2023)

Feature-preserving color pencil drawings from photographs

  • Dong Wang,
  • Guiqing Li,
  • Chengying Gao,
  • Shengwu Fu,
  • Yun Liang

DOI
https://doi.org/10.1007/s41095-022-0320-6
Journal volume & issue
Vol. 9, no. 4
pp. 807 – 825

Abstract

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Abstract Color pencil drawing is well-loved due to its rich expressiveness. This paper proposes an approach for generating feature-preserving color pencil drawings from photographs. To mimic the tonal style of color pencil drawings, which are much lighter and have relatively lower saturation than photographs, we devise a lightness enhancement mapping and a saturation reduction mapping. The lightness mapping is a monotonically decreasing derivative function, which not only increases lightness but also preserves input photograph features. Color saturation is usually related to lightness, so we suppress the saturation dependent on lightness to yield a harmonious tone. Finally, two extremum operators are provided to generate a foreground-aware outline map in which the colors of the generated contours and the foreground object are consistent. Comprehensive experiments show that color pencil drawings generated by our method surpass existing methods in tone capture and feature preservation.

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