Optimization of Space Color Mapping Using Compactly Supported Radial Basis Functions for Color Reproduction

  • Ladys Rodriguez
  • Luis Diago
  • Ichiro Hagiwara
Part of the Communications in Computer and Information Science book series (CCIS, volume 323)


Colors play an important role for customers to find their preference. The perception of the color depends on the devices used to show the colors and it changes with the color transformation between one device and another. This paper proposes an optimization of the Compactly-Supported Radial Basis Functions (CSRBF) space mapping to minimize the error in the color conversion between the system and the printer color spaces. A clustering k-means method is used to select the representative data in the printer color space to reproduce the whole space with high accuracy. The calculation of optimized CSRBF parameters using the representative data is proposed to minimize the color difference between the predicted CSRBF color value and the printed color value of all data in the printer color space. Proposed optimization method finds the optimized CSRBF parameters values and the optimal weighting parameters for color differences evaluation.


Radial Basis Function Color Space Radial Basis Function Color Conversion Propose Optimization Method 
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  1. 1.
    Cheol-Hee, L., Yeong-Ho, H.: Parametric Gamut Mapping Algorithms Using Variable Anchor Points. Journal of Imaging Science and Technology 44(1), 68–89 (2000)Google Scholar
  2. 2.
    Tominaga, S.: Color control of printers by neural networks. Journal of Electronic Imaging 7 (1998)Google Scholar
  3. 3.
    Qiao, Y.: Linear processing in color conversion. United States Patent Application Publication No. US2010/0157397 A1 (2010)Google Scholar
  4. 4.
    Savchenko, V., Pasko, A., Kunii, T.L., Savchenko, A.: Function representation of solids reconstructed from scattered surface points and contours. Computer Graphics Forum 14(4), 181–188 (1995)CrossRefGoogle Scholar
  5. 5.
    Wendland, H.: Piecewise polynomial, positive definite and compactly supported radial basis functions of minimal degree. Advances in Computational Mathematics 4, 389–396 (1995)zbMATHMathSciNetCrossRefGoogle Scholar
  6. 6.
    Brenner, S., Scott, L.: The mathematical theory of finite elements. Springer, New York (1994)CrossRefGoogle Scholar
  7. 7.
    CIE, Improvement to industrial colour-difference evaluation, CIE Publication No. 142-2001, Central Bureau of the CIE (2001)Google Scholar
  8. 8.
    CHROMiX, Delta-E: The Color Difference, CHROMiX ColorNews Issue No. 17 (2005)Google Scholar
  9. 9.
    Levenberg, K.: A method for the solution of certain non-linear problems in least squares. The Quarterly of Applied Mathematics 2, 164–168 (1944)zbMATHMathSciNetGoogle Scholar
  10. 10.
    Sijie, S.: An investigation of texture effects on instrumental and visual colour difference evaluation, pp. 1–331. Hong Kong Polytechnic University, Hong Kong (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ladys Rodriguez
    • 1
  • Luis Diago
    • 2
  • Ichiro Hagiwara
    • 1
    • 2
  1. 1.Institute for Advanced Study of Mathematical Sciences (MIMS)Meiji UniversityTama-kuJapan
  2. 2.Department of Mechanical Science and EngineeringTokyo Institute of TechnologyMeguro-kuJapan

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