TY - GEN
T1 - Pairwise Markov model applied to unsupervised image separation
AU - Rafi, Selwa
AU - Castella, Marc
AU - Pieczynski, Wojciech
PY - 2011/1/1
Y1 - 2011/1/1
N2 - The paper deals with blind separation and recovery of a noisy mixture of two binary signals on two sensors. Such a model can be applied in the context of recovery of scanned documents subject to show-through and bleed-through effects. The problem can be considered as a blind source separation one. Due to a complex noise and data structure, it is tackled from the more general approach of Bayesian restoration. The data is assumed to follow a Pairwise Markov Chain model: it generalizes Hidden Markov Chain models but it still allows one to calculate the a posteriori distributions of the data. The Expectation- Maximization (EM) and Iterative Conditional Estimation (ICE) methods are considered for parameter estimation, yielding an unsupervised processing. Finally, simulations show the interest of our approach on simulated and real data.
AB - The paper deals with blind separation and recovery of a noisy mixture of two binary signals on two sensors. Such a model can be applied in the context of recovery of scanned documents subject to show-through and bleed-through effects. The problem can be considered as a blind source separation one. Due to a complex noise and data structure, it is tackled from the more general approach of Bayesian restoration. The data is assumed to follow a Pairwise Markov Chain model: it generalizes Hidden Markov Chain models but it still allows one to calculate the a posteriori distributions of the data. The Expectation- Maximization (EM) and Iterative Conditional Estimation (ICE) methods are considered for parameter estimation, yielding an unsupervised processing. Finally, simulations show the interest of our approach on simulated and real data.
KW - Blind source separation
KW - Image separation
KW - Pairwise Markov Chain
KW - Show-through removal
UR - https://www.scopus.com/pages/publications/79958122992
U2 - 10.2316/P.2011.721-044
DO - 10.2316/P.2011.721-044
M3 - Conference contribution
AN - SCOPUS:79958122992
SN - 9780889868656
T3 - Proceedings of the 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2011
SP - 134
EP - 140
BT - Proceedings of the 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2011
PB - Acta Press
ER -