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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"/>
      <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/CIC.2009.17.1.art00052</article-id>
      <article-id pub-id-type="sici">2166-9635(20090101)2009:1L.284;1-</article-id>
      <article-id pub-id-type="publisher-id">cic_v2009n1/splitsection52.xml</article-id>
      <article-id pub-id-type="other">/ist/cic/2009/00002009/00000001/art00052</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Color Transforms for Creative Image Editing</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Kisilev</surname>
            <given-names>Pavel</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Freedman</surname>
            <given-names>Daniel</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>01</day>
        <month>01</month>
        <year>2009</year>
      </pub-date>
      <volume>2009</volume>
      <issue>1</issue>
      <fpage>284</fpage>
      <lpage>289</lpage>
      <permissions>
        <copyright-year>2009</copyright-year>
      </permissions>
      <abstract>
        <p>In this paper, we present a unified approach for the problem of computing color transforms, applications of which include shadow removal, object recoloring, and scene relighting. The detection of source and target regions is performed using a Bayesian classifier. Given these regions,
 the computed transform alters the color properties of the target region so as to closely resemble those of the source region. The proposed probabilistic formulation leads to a linear program (similar to the classic Transportation Problem), which computes the desired transformation between
 the target and source distributions. This formulation allows the target region to acquire the properties of the source region, while at the same time retaining its own look and feel. Promising results are shown for a variety of applications.</p>
      </abstract>
    </article-meta>
  </front>
</article>
