In this paper we study a Blind Source Separation (BSS) problem, and in particular we deal with document restoration. We consider the classical linear model. To this aim, we analyze the derivatives of the images instead of the intensity levels. Thus, we establish non-overlapping constraints on document sources. Moreover, we impose that the rows of the mixture matrices of the sources have sum equal to 1, in order to keep equal the lightnesses of the estimated sources and those of the data. Here we give a technique which uses the symmetric factorization, whose goodness is tested by the experimental results.
A Blind Source Separation Technique for Document Restoration Based on Image Discrete Derivative
Boccuto A.;Gerace I.
;Giorgetti V.;
2022
Abstract
In this paper we study a Blind Source Separation (BSS) problem, and in particular we deal with document restoration. We consider the classical linear model. To this aim, we analyze the derivatives of the images instead of the intensity levels. Thus, we establish non-overlapping constraints on document sources. Moreover, we impose that the rows of the mixture matrices of the sources have sum equal to 1, in order to keep equal the lightnesses of the estimated sources and those of the data. Here we give a technique which uses the symmetric factorization, whose goodness is tested by the experimental results.File in questo prodotto:
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