http://www.cnr.it/ontology/cnr/individuo/prodotto/ID91141
Blind separation of auto-correlated images from noisy mixtures using MRF models (Contributo in atti di convegno)
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- Blind separation of auto-correlated images from noisy mixtures using MRF models (Contributo in atti di convegno) (literal)
- Anno
- 2003-01-01T00:00:00+01:00 (literal)
- Alternative label
Tonazzini A. 1, Bedini L. 2, Kuruoglu E.E. 3, Salerno E.4 (2003)
Blind separation of auto-correlated images from noisy mixtures using MRF models
in 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Nara
(literal)
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- Tonazzini A. 1, Bedini L. 2, Kuruoglu E.E. 3, Salerno E.4 (literal)
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- This paper deals with the blind separation and reconstruction of
source images from mixtures with unknown coefficients, in presence
of noise. We address the blind source separation problem within
the ICA approach, i.e. assuming the statistical independence of
the sources, and reformulate it in a Bayesian estimation
framework. In this way, the flexibility of the Bayesian
formulation in accounting for prior knowledge can be exploited to
describe correlation within the individual source images, through
the use of suitable Gibbs priors. We propose a MAP estimation
method and derive a general algorithm for recovering both the
mixing matrix and the sources, based on alternating maximization
within a simulated annealing scheme. We experimented with this
scheme on both synthetic and real images, and found that a source
model accounting for correlation is able to increase robustness
against noise. (literal)
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- Blind separation of auto-correlated images from noisy mixtures using MRF models (literal)
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