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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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