Historic document image de-noising using principal component analysis (PCA) and local pixel grouping (LPG)

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Abstract

In this paper, an approach of principal component analysis (PCA) with local pixel grouping (LPG) is used to de-noising the noisy historical document image. This technique ensures the preservation of historic document image local structure. This is due to block matching based LPG which carries out classification to allow only the sample blocks with similar contents used in the calculation for PCA transform estimation. Such an LPG procedure ensures that the image local features can be well preserved after the noise removing process in the PCA domain. The LPG-PCA de-noising procedure will repeat one more times with adaptively adjusted noise level to further improve the performance of de-noising the historic document image. The experiment results show that LPG-PCA model has good results in de-noising historical document image.

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Tang, H. Y., Muda, A. K., Choo, Y. H., Muda, N. A., & Azmi, M. S. (2017). Historic document image de-noising using principal component analysis (PCA) and local pixel grouping (LPG). In Advances in Intelligent Systems and Computing (Vol. 557, pp. 77–87). Springer Verlag. https://doi.org/10.1007/978-3-319-53480-0_8

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