Skip to main content
Article thumbnail
Location of Repository

Separating a Real-Life Nonlinear Image Mixture

By Luis B. Almeida


When acquiring an image of a paper document, the image printed on the back page sometimes shows through. The mixture of the front- and back-page images thus obtained is markedly nonlinear, and thus constitutes a good real-life test case for nonlinear blind source separation. This paper addresses a difficult version of this problem, corresponding to the use of "onion skin" paper, which results in a relatively strong nonlinearity of the mixture, which becomes close to singular in the lighter regions of the images. The separation is achieved through the MISEP technique, which is an extension of the well known INFOMAX method. The separation results are assessed with objective quality measures. They show an improvement over the results obtained with linear separation, but have room for further improvement

Topics: Statistical Models, Machine Learning, Neural Nets, Artificial Intelligence
Year: 2005
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • (external link)
  • Suggested articles


    1. (1998). A survey of medical image registration. Medical Image Analysis, doi
    2. (1995). An information-maximization approach to blind separation and blind deconvolution.
    3. (2002). An unsupervised ensemble learning method for nonlinear dynamic state-space models. doi
    4. (1953). Analyse ge´ne´rale des liaisons stochastiques.
    5. (1999). Analysis and Signal Separation,
    6. (2003). Application of independent component analysis to microarrays.
    7. (2000). Bayesian nonlinear independent component analysis by multi-layer perceptrons.
    8. (1992). Blind separation of sources: A nonlinear neural algorithm.
    9. (0661). Estimating mutual information. Physical Review E,
    10. (2003). Faster training in nonlinear ICA using MISEP.
    11. (2002). Image denoising using SOM-based nonlinear independent component analysis.
    12. (1994). Independent component analysis – a new concept?
    13. (1999). Independent Component Analysis and Signal Separation, doi
    14. (2000). Independent component analysis: Algorithms and applications. Neural Networks,
    15. (2003). Kernel-based nonlinear blind source separation.
    16. (1992). Learning factorial codes by predictability minimization. doi
    17. (1997). Maximum likelihood blind source separation: A context-sensitive generalization of ica.
    18. (2003). MISEP – Linear and nonlinear ICA based on mutual information.
    19. (2003). Nonlinear geometric ICA. doi
    20. (1995). Nonlinear higher-order statistical decorrelation by volumeconserving neural architectures.
    21. (1999). Nonlinear independent component analysis: Existence and uniqueness results.
    22. (2004). Separating a Real-Life Nonlinear Image Mixture
    23. (2004). Separating a real-life nonlinear mixture of images. In
    24. (1999). Source separation in post-nonlinear mixtures. doi

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.