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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010350</journal-id>
      <journal-title>Color and Imaging Conference</journal-title>
      <abbrev-journal-title>color imaging conf</abbrev-journal-title>
      <issn pub-type="ppub">2166-9635</issn><issn pub-type="epub"></issn>
      <publisher>
        <publisher-name>Society for Imaging Science and Technology</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.2352/ISSN.2169-2629.2018.26.91</article-id>
      <article-id pub-id-type="sici">2166-9635(20181112)2018:1L.91;1-</article-id>
      <article-id pub-id-type="publisher-id">s16.phd</article-id>
      <article-id pub-id-type="other">/ist/cic/2018/00002018/00000001/art00016</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Reversible Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness for Image Enhancement</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Ji Cho</surname>
            <given-names>Yoon</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Cui</surname>
            <given-names>Guihua</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Sohn</surname>
            <given-names>Kwanghoon</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>12</day>
        <month>11</month>
        <year>2018</year>
      </pub-date>
      <volume>2018</volume>
      <issue>1</issue>
      <fpage>91</fpage>
      <lpage>95</lpage>
      <permissions>
        <copyright-year>2018</copyright-year>
      </permissions>
      <abstract>
        <p>New reversible saturation, vividness, blackness and whiteness models were developed based on a visual data. The aim of this study is to develop a model that can be applicable to imaging devices and to enhance the images by controlling one of the scales. It was found that the models
 gave good predictions with the NCS (Natural Colour System) data. The newly developed models are applicable to colour image evaluation and image enhancement.</p>
      </abstract>
    </article-meta>
  </front>
</article>
