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Kayabol, Koray; Kuruoglu, Ercan E.; Sankur, Bulent
{
"@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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