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2004
IEEE

Joint blind separation and restoration of mixed degraded images for document analysis

10 years 3 months ago
Joint blind separation and restoration of mixed degraded images for document analysis
We consider the problem of extracting clean images from noisy mixtures of images degraded by blur operators. This special case of source separation arises, for instance, when analyzing document images showing bleed-through or showthrough. We propose to jointly perform demixing and deblurring by augmenting blind source separation with a step of image restoration. Within the ICA approach, i.e. assuming the statistical independence of the sources, we adopt a Bayesian formulation were the priors on the ideal images are given in the form of MRF, and a MAP estimation is employed for the joint recovery of the mixing matrix and the images. We show that taking into account for the blur model and for a proper image model improves the separation process and makes it more robust against noise. Preliminary results on synthetic examples of documents exhibiting bleedthrough are provided, considering edge-preserving priors that are suitable to describe text images.
Anna Tonazzini, Ivan Gerace, Francesco Cricco
Added 24 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2004
Where ICIP
Authors Anna Tonazzini, Ivan Gerace, Francesco Cricco
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