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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/J.ImagingSci.Technol.2017.61.4.040402</article-id>
      <article-id pub-id-type="sici">2166-9635(20170911)2017:25L.20;1-</article-id>
      <article-id pub-id-type="publisher-id">s5.phd</article-id>
      <article-id pub-id-type="other">/ist/cic/2017/00002017/00000025/art00005</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Image Quality Metrics for the Evaluation and Optimization of Capsule Video Endoscopy Enhancement Techniques</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Pedersen</surname>
            <given-names>Marius</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Cherepkova</surname>
            <given-names>Olga</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Mohammed</surname>
            <given-names>Ahmed</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>11</day>
        <month>09</month>
        <year>2017</year>
      </pub-date>
      <volume>2017</volume>
      <issue>25</issue>
      <fpage>20</fpage>
      <lpage>27</lpage>
      <permissions>
        <copyright-year>2017</copyright-year>
      </permissions>
      <abstract>
        <p>Capsule endoscopy, using a wireless camera to capture the digestive track, is becoming a popular alternative to traditional colonoscopy. The images obtained from a capsule have lower quality compared to traditional colonoscopy, and high-quality images are required by medical doctors
 in order to set an accurate diagnosis. Over the last years several enhancement techniques have been proposed to improve the quality of capsule images. In order to verify that the capsule images have the required diagnostic quality some kind of quality assessment is required. In this work,
 the authors evaluate state-of-the-art no-reference image quality metrics for capsule video endoscopy. Furthermore, they use the best performing metric to optimize one of the capsule video endoscopy enhancement methods and validate through subjective experiment. © 2017 Society for Imaging
 Science and Technology.</p>
      </abstract>
    </article-meta>
  </front>
</article>
