Spatio-temporal regularized shock-diffusion filtering with local entropy for restoration of degraded document images

Abstract

This paper proposes a novel model for restoration of document images with degraded background caused by show-through/smear or deteriorated documents. The model is formulated as a partial differential equation (PDE) that consists of spatio-temporal regularization of shock filtering and diffusion process, as well as local entropy. Shock filtering is employed to enhance the brightness contrast between texts and background according to image gradients adaptively. Diffusion process is not only responsible for removing selectively noise in the input image, but also suppressing the amplified noise by the shock filtering. Local entropy based source term serves as degradation-corrected term that is responsible for reducing the influence of degradation. A splitting-based algorithm is developed to solve the proposed model numerically, where two typical splitting methods and finite difference are combined. We test the proposed model and numerical scheme on DIBCO 2009–2014 and 2016 datasets. Experimental results indicate that the proposed method works well in restoring document images with degraded background, and achieves comparable performances compared to seven relevant methods for seven DIBCO datasets.