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Image Source Separation Using Color Channel Dependencies

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


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{
  "@context": "https://schema.org/", 
  "@id": 38431, 
  "@type": "ScholarlyArticle", 
  "creator": [
    {
      "@type": "Person", 
      "affiliation": "CNR, ISTI, Via G Moruzzi 1, I-56124 Pisa, Italy", 
      "name": "Kayabol, Koray"
    }, 
    {
      "@type": "Person", 
      "affiliation": "CNR, ISTI, Via G Moruzzi 1, I-56124 Pisa, Italy", 
      "name": "Kuruoglu, Ercan E."
    }, 
    {
      "@type": "Person", 
      "affiliation": "Bogazici Univ, Istanbul 80815, Turkey", 
      "name": "Sankur, Bulent"
    }
  ], 
  "datePublished": "2009-01-01", 
  "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.", 
  "headline": "Image Source Separation Using Color Channel Dependencies", 
  "identifier": 38431, 
  "image": "https://aperta.ulakbim.gov.tr/static/img/logo/aperta_logo_with_icon.svg", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "name": "Image Source Separation Using Color Channel Dependencies", 
  "url": "https://aperta.ulakbim.gov.tr/record/38431"
}
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