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Adding Local Contrast to Global Gamut Mapping Algorithms

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This paper deals with the potential of spatial gamut mapping methods as a complement to global gamut mapping algorithms. The main goal is to recover the original local contrast between neighboring pixels in addition to the usual optimization of preserving lightness, saturation and global contrast. As a typical representative for such a spatial mapping concept, we study unsharp masking applied to an image of the difference of the original and the result of a given gamut mapping algorithm. Thereby an edge preserving smoothing algorithm is used to avoid halo artefacts. In our psychophysical experiments every considered gamut mapping algorithm shows a significant gain in preference by our local contrast approach. The presented method can be seen as an additional feature towards an image-to-device gamut mapping design.
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Document Type: Research Article

Publication date: January 1, 2006

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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