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Space-dependent color gamut mapping: a variational approach.

Ron Kimmel1, Doron Shaked, Michael Elad

  • 1Computer Science Department, The Technion-Israel Institute of Technology, Haifa 32000, Israel.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|June 24, 2005
PubMed
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This study introduces a novel variational approach for space-dependent gamut mapping, optimizing color image reproduction for printing. The method offers an efficient solution for accurately fitting images into device color gamuts.

Area of Science:

  • Computer Vision
  • Image Processing
  • Color Science

Background:

  • Gamut mapping adjusts color images for specific rendering mediums, crucial for accurate print reproduction.
  • Traditional methods often ignore spatial color information, while recent spatial-dependent approaches can be computationally expensive or heuristic.
  • Existing methods struggle to balance spectral and spatial perceptual measures effectively.

Purpose of the Study:

  • To present a new variational approach for space-dependent gamut mapping.
  • To introduce a novel measure for gamut mapping problems, linking spectral and spatial perceptual qualities.
  • To develop an efficient numerical solution for gamut mapping.

Main Methods:

  • A variational approach is proposed for space-dependent gamut mapping.

Related Experiment Videos

  • A new measure, related to Retinex and coupling spectral-spatial perception, is introduced.
  • The problem is formulated as a quadratic programming problem, ensuring a unique solution for convex gamuts.

    • Main Results:

    • The proposed method offers a novel measure for gamut mapping.
    • The formulation as a quadratic programming problem guarantees a unique solution under specific conditions.
    • An efficient numerical solution is presented with promising experimental results.

    Conclusions:

    • The developed variational approach provides an effective method for space-dependent gamut mapping.
    • The technique offers a computationally efficient and perceptually relevant solution for color reproduction.
    • This work advances the field by integrating spatial and spectral color information in gamut mapping.