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Retaining local image information in gamut mapping algorithms.

Peter Zolliker1, Klaus Simon

  • 1Empa, Swiss Federal Laboratories for Materials Testing and Research, Laboratory for Media Technology, CH-8600 Dübendorf, Switzerland. peter.zolliker@empa.ch

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|March 16, 2007
PubMed
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This study enhances gamut mapping algorithms by combining global and spatial methods to preserve local image contrast and reduce artifacts. Psycho-visual experiments confirm the effectiveness of this novel approach for applications like newspaper printing.

Area of Science:

  • Image Processing
  • Computer Vision
  • Color Science

Background:

  • Gamut mapping algorithms aim to reproduce images in smaller color spaces.
  • Existing methods often struggle to preserve local image details and contrast.
  • Artifacts like halos can be introduced during the gamut mapping process.

Purpose of the Study:

  • To develop a gamut mapping algorithm that preserves local image information, including local contrast.
  • To minimize artifacts introduced by the gamut mapping process.
  • To improve upon existing global gamut mapping techniques by integrating spatial methods.

Main Methods:

  • A novel approach combining global gamut mapping with spatial techniques.
  • Implementation of an unsharp masking technique utilizing an edge-preserving smoothing algorithm.

Related Experiment Videos

  • Validation through psycho-visual experiments on newspaper printing (a small destination gamut).

    • Main Results:

    • Successful recovery of local contrast between neighboring pixels.
    • Effective avoidance of halo artifacts through the proposed edge-preserving smoothing.
    • Demonstrated improvement in mapping properties, evidenced by local mapping histograms.

    Conclusions:

    • The combined global and spatial gamut mapping approach effectively preserves local image information and contrast.
    • The proposed unsharp masking technique successfully mitigates artifacts.
    • The method shows significant promise for applications with small destination gamuts.