Bleed-through is a commonly encountered degradation in ancient printed documents and manuscripts, which severely impair their readability. Digital image restoration techniques can be effective to remove or significantly reduce this degradation. In bleed-through document image restoration the main issue is to identify the bleed-through pixels and replace them with appropriate values, in accordance to their surroundings. In this paper, we propose a two stage method, where a pair of properly registered images of the document recto and verso is first used to locate the bleed-through pixels in each side, and then a sparse representation based image inpainting technique is used to fill-in the bleed-through areas according to the neighbourhood, in such a way to preserve the original appearance of the document. The advantages of the proposed inpainting technique over state-of-the-art methods are illustrated by the improvement in the visual results.
Sparse representation based inpainting for the restoration of document images affected by bleed-through
Tonazzini A;Savino P;Salerno E
2018
Abstract
Bleed-through is a commonly encountered degradation in ancient printed documents and manuscripts, which severely impair their readability. Digital image restoration techniques can be effective to remove or significantly reduce this degradation. In bleed-through document image restoration the main issue is to identify the bleed-through pixels and replace them with appropriate values, in accordance to their surroundings. In this paper, we propose a two stage method, where a pair of properly registered images of the document recto and verso is first used to locate the bleed-through pixels in each side, and then a sparse representation based image inpainting technique is used to fill-in the bleed-through areas according to the neighbourhood, in such a way to preserve the original appearance of the document. The advantages of the proposed inpainting technique over state-of-the-art methods are illustrated by the improvement in the visual results.File | Dimensione | Formato | |
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