<!DOCTYPE article PUBLIC '-//NLM//DTD Journal Publishing DTD v2.1 20050630//EN' 'http://uploads.ingentaconnect.com/docs/dtd/ingenta-journalpublishing.dtd'>
<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.2169-2629.2020.28.14</article-id>
      <article-id pub-id-type="sici">2166-9635(20201104)2020:28L.100;1-</article-id>
      <article-id pub-id-type="publisher-id">s15.phd</article-id>
      <article-id pub-id-type="other">/ist/cic/2020/00002020/00000028/art00015</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A Tone Mapping Model Based on Receptive Field for HDR Images</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Mehmood</surname>
            <given-names>Imran</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Khan</surname>
            <given-names>Muhammad Usman</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Mughal</surname>
            <given-names>Muhammad Farhan</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Luo</surname>
            <given-names>Ming Ronnier</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>100</fpage>
      <lpage>104</lpage>
      <permissions>
        <copyright-year>2020</copyright-year>
      </permissions>
      <abstract>
        <p>High dynamic range (HDR) imaging has greater contrast reproduction capability than standard imaging techniques. It can achieve natural and pleasing appearance in terms of image quality. A tone mapping model (TMOz) is developed based on the center-surround properties of the mammalian
 ganglion cells of the human visual system for feature enhancement. The contrast of the HDR image is mapped adaptively to an SDR display range using a global method followed by contrast enhancement in local regions. A psychophysical experiment was conducted to refine the model for adaptivity
 of the contrast mapping function. Finally, the performance of the TMOz was evaluated using CIELAB (2:1) formula together with high quality reference images. The results showed that TMOz outperformed the other tone mapping operators (TMOs).</p>
      </abstract>
      <kwd-group>
        <kwd>HDR</kwd>
        <kwd>TMO</kwd>
        <kwd>LOGARITHMIC TONE MAPPING</kwd>
        <kwd>RECEPTIVE FIELD</kwd>
        <kwd>ADAPTIVE TONE MAPPING</kwd>
        <kwd>IMAGE QUALITY</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
