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Image Source Separation Using Color Channel Dependencies

Kayabol, Koray; Kuruoglu, Ercan E.; Sankur, Bulent


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  <dc:creator>Kayabol, Koray</dc:creator>
  <dc:creator>Kuruoglu, Ercan E.</dc:creator>
  <dc:creator>Sankur, Bulent</dc:creator>
  <dc:date>2009-01-01</dc:date>
  <dc:description>We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of color images which have dependence between its components. A Markov Random Field (MRF) is used for modeling of the inter and intra-source local correlations. We. resort to Gibbs sampling algorithm for obtaining the MAP estimate of the sources since non-Gaussian priors are adopted. We test the performance of the proposed method both oil synthetic color texture mixtures and a realistic color scene captured with a spurious reflection.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/38431</dc:identifier>
  <dc:identifier>oai:zenodo.org:38431</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:title>Image Source Separation Using Color Channel Dependencies</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
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