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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010351</journal-id>
      <journal-title>Conference on Colour in Graphics, Imaging, and Vision</journal-title>
      <abbrev-journal-title>conf colour graph imag vis</abbrev-journal-title>
      <issn pub-type="ppub">2158-6330</issn><issn pub-type="epub"/>
      <publisher>
        <publisher-name>Society of Imaging Science and Technology</publisher-name>
        <publisher-loc>7003 Kilworth Lane, Springfield, VA 22151, USA</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta><article-id pub-id-type="doi">10.2352/CGIV.2006.3.1.art00051</article-id>
      <article-id pub-id-type="sici">2158-6330(20060101)2006:1L.257;1-</article-id>
      <article-id pub-id-type="publisher-id">cgiv_v2006n1/splitsection51.xml</article-id>
      <article-id pub-id-type="other">/ist/cgiv/2006/00002006/00000001/art00051</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Adding Local Contrast to Global Gamut Mapping Algorithms</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Zolliker</surname>
            <given-names>Peter</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Simon</surname>
            <given-names>Klaus</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>01</day>
        <month>01</month>
        <year>2006</year>
      </pub-date>
      <volume>2006</volume>
      <issue>1</issue>
      <fpage>257</fpage>
      <lpage>261</lpage>
      <permissions>
        <copyright-year>2006</copyright-year>
      </permissions>
      <abstract>
        <p>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.</p>
      </abstract>
    </article-meta>
  </front>
</article>
