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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010351</journal-id>
      <journal-title>Conference on Colour in Graphics, Imaging, and Vision</journal-title>
      <abbrev-journal-title>conf colour graph imag vis</abbrev-journal-title>
      <issn pub-type="ppub">2158-6330</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/CGIV.2004.2.1.art00099</article-id>
      <article-id pub-id-type="sici">2158-6330(20040101)2004:1L.494;1-</article-id>
      <article-id pub-id-type="publisher-id">cgiv_v2004n1/splitsection99.xml</article-id>
      <article-id pub-id-type="other">/ist/cgiv/2004/00002004/00000001/art00099</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>PCA Component Mixing for Watermark Embedding in Spectral Images</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Kaarna</surname>
            <given-names>Arto</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Botchko</surname>
            <given-names>Vladimir</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Galibarov</surname>
            <given-names>Pavel</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>01</day>
        <month>01</month>
        <year>2004</year>
      </pub-date>
      <volume>2004</volume>
      <issue>1</issue>
      <fpage>494</fpage>
      <lpage>498</lpage>
      <permissions>
        <copyright-year>2004</copyright-year>
      </permissions>
      <abstract>
        <p>This study considers watermark embedding in spectral images. The embedding takes place in a transform space which is obtained through the Principal Component Analysis (PCA). The watermark is embedded in one eigenimage by mixing one eigenimage and the watermark. The watermark is a visual
 watermark which spreads to all bands of the image after the inverse PCA-transform. This new method is a generalization of an existing method. Our experiments indicate that a suitable set of parameter values allows better embedding than the methods compared.</p>
      </abstract>
    </article-meta>
  </front>
</article>
