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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010604</journal-id>
      <journal-title>Electronic Imaging</journal-title>
      <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub"></issn>
      <publisher>
        <publisher-name>Society for 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/ISSN.2470-1173.2019.14.COLOR-086</article-id>
      <article-id pub-id-type="sici">2470-1173(20190113)2019:14L.861;1-</article-id>
      <article-id pub-id-type="publisher-id">ei_24701173_v2019n14_r1/s10.xml</article-id>
      <article-id pub-id-type="other">/ist/ei/2019/00002019/00000014/art00010</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Evaluating the Naturalness and Legibility of Whiteboard Image Enhancements</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Assefa</surname>
            <given-names>Mekides</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Yngve Hardeberg</surname>
            <given-names>Jon</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>13</day>
        <month>01</month>
        <year>2019</year>
      </pub-date>
      <volume>2019</volume>
      <issue>14</issue>
      <fpage>86-1</fpage>
      <lpage>86-9</lpage>
      <permissions>
        <copyright-year>2019</copyright-year>
      </permissions>
      <abstract>
        <p>
          <italic>Over the years, there have been many studies conducted for whiteboard image detection, extraction and quality enhancements. However, the image quality attributes of the streaming whiteboard contents as well as users’ expectations from such whiteboard scenes are not well investigated.
 Therefore, the primary goal of this work is to examine the effects of the different whiteboard image features on the overall quality of the whiteboard images. Particularly, the naturalness and legibility quality attributes of the images were investigated through psychovisual experiments. Our
 experimental results show that increasing color attributes such as saturation, brightness and luminance contrast, lead to more legible whiteboard contents; which in turn increases the whiteboard image quality. Enhancement processes of the whiteboard backgrounds, however, show strong effects
 on the naturalness attribute. But, when the general image quality is considered, observers tend to prefer more legible whiteboard image contents rather than the naturalness of the appearance.</italic>
        </p>
      </abstract>
      <kwd-group>
        <kwd>Whiteboard image quality</kwd>
        <kwd>Whiteboard image enhancement</kwd>
        <kwd>Image naturalness</kwd>
        <kwd>Whiteboard content readability</kwd>
        <kwd>Evaluation of whiteboard image quality</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
