Image source separation using color channel dependencies (Articolo in rivista)

Type
Label
  • Image source separation using color channel dependencies (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Alternative label
  • Kayabol K.; Kuruoglu E. E.; Sankur B. (2009)
    Image source separation using color channel dependencies
    in Lecture notes in computer science
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Kayabol K.; Kuruoglu E. E.; Sankur B. (literal)
Pagina inizio
  • 499 (literal)
Pagina fine
  • 506 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 5441 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: ICA 2009 - Independent Component Analysis and Signal Separation. 8th International Conference (Paraty, Brazil, 15-18 March 2009). Proceedings, pp. 499 - 506. (Lecture Notes in Computer Science, vol. 5441). Springer, 2009. (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Bogazici University, Turchia (literal)
Titolo
  • Image source separation using color channel dependencies (literal)
Abstract
  • 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 on synthetic color texture mixtures and a realistic color scene captured with a spurious reflection. (literal)
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