Document - Image source separation using color channel dependencies

2009

Conference article Open Access

Image source separation using color channel dependencies

Kayabol K, Kuruoglu E E, Sankur B

Bayesian source separation Image Processing and Computer Vision Markov Chain Monte Carlo 68-xx Computer science

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.

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BibTeX entry

@inproceedings{oai:it.cnr:prodotti:44286,
	title = {Image source separation using color channel dependencies},
	author = {Kayabol K and Kuruoglu E E and Sankur B},
	doi = {10.1007/978-3-642-00599-2_63},
	year = {2009}
}