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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.2169-2629.2020.28.55</article-id>
      <article-id pub-id-type="sici">2166-9635(20201104)2020:28L.347;1-</article-id>
      <article-id pub-id-type="publisher-id">s56.phd</article-id>
      <article-id pub-id-type="other">/ist/cic/2020/00002020/00000028/art00056</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Digital camera-based spectral estimation in open environment based on imaging condition correction</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Liang</surname>
            <given-names>Jinxing</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Xiao</surname>
            <given-names>Kaida</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>04</day>
        <month>11</month>
        <year>2020</year>
      </pub-date>
      <volume>2020</volume>
      <issue>28</issue>
      <fpage>347</fpage>
      <lpage>350</lpage>
      <permissions>
        <copyright-year>2020</copyright-year>
      </permissions>
      <abstract>
        <p>Digital camera-based spectral estimation in open environment is a challenge in current stage. Although some methods have been proposed in recent years, the methods do not consider the exposure inconsistency between camera spectral characterization and spectral estimation applications,
 that makes the proposed method cannot for practical applications. We proposed here a spectral estimation method based on imaging condition correction of which can deal with the problem exist in current methods. Using the whiteboard and raw camera response, the imaging conditions of open environment
 is recorded and corrected to the reference imaging conditions, and the surface spectral of object is estimated using the established spectral estimation matrix in the reference imaging conditions. The proposed method in three application models are tested and compared. The result shows that
 the adaptive model for imaging condition correction gives the best spectral estimation accuracy.</p>
      </abstract>
      <kwd-group>
        <kwd>DIGITAL CAMERA</kwd>
        <kwd>SPECTRAL ESTIMATION</kwd>
        <kwd>SPECTRAL MEASUREMENT</kwd>
        <kwd>OPEN ENVIRONMENT</kwd>
        <kwd>IMAGING CONDITION CORRECTION</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
