Colour Gamut Mapping as a Constrained Variational Problem

  • Ali Alsam
  • Ivar Farup
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5575)


We present a novel, computationally efficient, iterative, spatial gamut mapping algorithm. The proposed algorithm offers a compromise between the colorimetrically optimal gamut clipping and the most successful spatial methods. This is achieved by the iterative nature of the method. At iteration level zero, the result is identical to gamut clipping. The more we iterate the more we approach an optimal, spatial, gamut mapping result. Optimal is defined as a gamut mapping algorithm that preserves the hue of the image colours as well as the spatial ratios at all scales. Our results show that as few as five iterations are sufficient to produce an output that is as good or better than that achieved in previous, computationally more expensive, methods. Being able to improve upon previous results using such low number of iterations allows us to state that the proposed algorithm is O(N), N being the number of pixels. Results based on a challenging small destination gamut supports our claims that it is indeed efficient.


Original Image Colour Space Iteration Level Colour Pixel Contrast Sensitivity Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ali Alsam
    • 1
  • Ivar Farup
    • 2
  1. 1.Sør-Trøndelag University CollegeTrondheimNorway
  2. 2.Gjøvik University CollegeGjøvikNorway

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