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.

Source: Independent Component Analysis and Signal Separation. 8th International Conference, pp. 499–506, Paraty, Brazil, 15-18 March 2009

Publisher: Springer, Berlin , Germania

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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.},
	publisher = {Springer, Berlin , Germania},
	doi = {10.1007/978-3-642-00599-2_63},
	booktitle = {Independent Component Analysis and Signal Separation. 8th International Conference, pp. 499–506, Paraty, Brazil, 15-18 March 2009},
	year = {2009}
}