skip to main content
research-article

Practical pigment mixing for digital painting

Published:10 December 2021Publication History
Skip Abstract Section

Abstract

There is a significant flaw in today's painting software: the colors do not mix like actual paints. E.g., blue and yellow make gray instead of green. This is because the software is built around the RGB representation, which models the mixing of colored lights. Paints, however, get their color from pigments, whose mixing behavior is predicted by the Kubelka-Munk model (K-M). Although it was introduced to computer graphics almost 30 years ago, the K-M model has never been adopted by painting software in practice as it would require giving up the RGB representation, growing the number of per-pixel channels substantially, and depriving the users of painting with arbitrary RGB colors. In this paper, we introduce a practical approach that enables mixing colors with K-M while keeping everything in RGB. We achieve this by establishing a latent color space, where RGB colors are represented as mixtures ofprimary pigments together with additive residuals. The latents can be manipulated with linear operations, leading to expected, plausible results. We describe the conversion between RGB and our latent representation, and show how to implement it efficiently.

Skip Supplemental Material Section

Supplemental Material

a234-sochorova.mp4

mp4

100.3 MB

References

  1. Elad Aharoni-Mack, Yakov Shambik, and Dani Lischinski. 2017. Pigment-Based Recoloring of Watercolor Paintings. In Proceedings of NPAR '17. Article 1. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. William Baxter, Jeremy Wendt, and Ming C. Lin. 2004. IMPaSTo: A Realistic, Interactive Model for Paint. In Proceedings of NPAR '04. 45--56. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Roy S. Berns. 2016. Artist Paint Spectral Database. In Proceedings of CIC24.Google ScholarGoogle Scholar
  4. Peter Blaškovič. 2016. Rebelle: Real Watercolor and Acrylic Painting Software. In Proceedings of SIGGRAPH '16: ACM SIGGRAPH 2016 Appy Hour. Article 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. David Briggs. 2007. The Dimensions of Colour. http://www.huevaluechroma.comGoogle ScholarGoogle Scholar
  6. Richard H. Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu. 1995. A Limited Memory Algorithm for Bound Constrained Optimization. SIAM Journal on Scientific Computing 16, 5 (1995), 1190--1208. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Zhili Chen, Byungmoon Kim, Daichi Ito, and Huamin Wang. 2015. Wetbrush: GPU-based 3D Painting Simulation at the Bristle Level. ACM Transactions on Graphics 34, 6, Article 200 (2015). Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Nelson S.-H. Chu and Chiew-Lan Tai. 2005. MoXi: Real-Time Ink Dispersion in Absorbent Paper. ACM Transactions on Graphics 24, 3 (2005), 504--511. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. CIE. 2001. Improvement to industrial colour-difference evaluation. Central Bureau of the CIE, Vienna, Austria.Google ScholarGoogle Scholar
  10. Cassidy J. Curtis, Sean E. Anderson, Joshua E. Seims, Kurt W. Fleischer, and David H. Salesin. 1997. Computer-Generated Watercolor. In Proceedings of SIGGRAPH '97. 421--430. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. D. R. Duncan. 1940. The colour of pigment mixtures. Proceedings of the Physical Society 52 (1940), 390--400.Google ScholarGoogle ScholarCross RefCross Ref
  12. Nathan Gossett and Baoquan Chen. 2004. Paint Inspired Color Mixing and Compositing for Visualization. In Proceedings of InfoVis '04. 113--118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Andreas Griewank and Andrea Walther. 2008. Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. SIAM, Philadelphia, PA, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Chet S. Haase and Gary W. Meyer. 1992. Modeling Pigmented Materials for Realistic Image Synthesis. ACM Transactions on Graphics 11, 4 (1992), 305--335. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. William Van Haevre, Tom Van Laerhoven, Fabian Di Fiore, and Frank Van Reeth. 2007. From Dust Till Drawn. The Visual Computer 23, 9--11 (2007), 925--934. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Georg A. Klein. 2010. Industrial Color Physics. Springer, New York, NY, USA.Google ScholarGoogle Scholar
  17. Paul Kubelka and Franz Munk. 1931. Ein Beitrag zur Optik der Farbanstriche. Zeitschrift für Technishen Physik 12 (1931), 593--601.Google ScholarGoogle Scholar
  18. Jingwan Lu, Stephen DiVerdi, Willa Chen, Connelly Barnes, and Adam Finkelstein. 2014. RealPigment: Paint Compositing by Example. In Proceedings of NPAR. 21--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Ján Morovič. 2008. Color Gamut Mapping. Wiley, Chichester, West Sussex, UK. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Yoshio Okumura. 2005. Developing a Spectral and Colorimetric Database of Artist Paint Materials. Master's thesis. Rochester Institute of Technology.Google ScholarGoogle Scholar
  21. Björn Ottosson. 2020. A perceptual color space for image processing. https://bottosson.github.io/posts/oklabGoogle ScholarGoogle Scholar
  22. Michael R. Pointer. 1980. The Gamut of Real Surface Colours. Color Research and Application 5, 3 (1980), 145--155.Google ScholarGoogle ScholarCross RefCross Ref
  23. J. L. Saunderson. 1942. Calculation of the color of pigmented plastics. Journal of the Optical Society of America 32 (1942), 727--736.Google ScholarGoogle ScholarCross RefCross Ref
  24. Maria Shugrina, Amlan Kar, Sanja Fidler, and Karan Singh. 2020. Nonlinear Color Triads for Approximation, Learning and Direct Manipulation of Color Distributions. ACM Transactions on Graphics 39, 4, Article 97 (2020).Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Lionel Simonot and Methieu Hébert. 2014. Between additive and subtractive color mixings: intermediate mixing models. Journal of the Optical Society of America A 31, 1 (2014), 58--66.Google ScholarGoogle ScholarCross RefCross Ref
  26. Junichi Sugita and Tokiichiro Takahashi. 2017. Computational RYB Color Model and its Applications. IIEEJ Transactions on Image Electronics and Visual Computing 5, 2 (2017), 110--122.Google ScholarGoogle Scholar
  27. Jianchao Tan, Stephen DiVerdi, Jingwan Lu, and Yotam Gingold. 2019. Pigmento: Pigment-Based Image Analysis and Editing. IEEE Transactions on Visualization and Computer Graphics 25, 9 (2019).Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Practical pigment mixing for digital painting

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Graphics
        ACM Transactions on Graphics  Volume 40, Issue 6
        December 2021
        1351 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/3478513
        Issue’s Table of Contents

        Copyright © 2021 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 10 December 2021
        Published in tog Volume 40, Issue 6

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader