Next Article in Journal
Applications of Laboratory-Based Phase-Contrast Imaging Using Speckle Tracking Technique towards High Energy X-Rays
Next Article in Special Issue
Slant Removal Technique for Historical Document Images
Previous Article in Journal
Radio Frequency Modeling of Receive Coil Arrays for Magnetic Resonance Imaging
Previous Article in Special Issue
Text/Non-Text Separation from Handwritten Document Images Using LBP Based Features: An Empirical Study
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
J. Imaging 2018, 4(5), 68;

Non-Local Sparse Image Inpainting for Document Bleed-Through Removal

Institute of Information Science and Technologies, Italian National Research Council, 56124 Pisa, Italy
Author to whom correspondence should be addressed.
Received: 14 January 2018 / Revised: 26 March 2018 / Accepted: 26 April 2018 / Published: 9 May 2018
(This article belongs to the Special Issue Document Image Processing)
Full-Text   |   PDF [7116 KB, uploaded 24 May 2018]   |  


Bleed-through is a frequent, pervasive degradation in ancient manuscripts, which is caused by ink seeped from the opposite side of the sheet. Bleed-through, appearing as an extra interfering text, hinders document readability and makes it difficult to decipher the information contents. Digital image restoration techniques have been successfully employed to remove or significantly reduce this distortion. This paper proposes a two-step restoration method for documents affected by bleed-through, exploiting information from the recto and verso images. First, the bleed-through pixels are identified, based on a non-stationary, linear model of the two texts overlapped in the recto-verso pair. In the second step, a dictionary learning-based sparse image inpainting technique, with non-local patch grouping, is used to reconstruct the bleed-through-contaminated image information. An overcomplete sparse dictionary is learned from the bleed-through-free image patches, which is then used to estimate a befitting fill-in for the identified bleed-through pixels. The non-local patch similarity is employed in the sparse reconstruction of each patch, to enforce the local similarity. Thanks to the intrinsic image sparsity and non-local patch similarity, the natural texture of the background is well reproduced in the bleed-through areas, and even a possible overestimation of the bleed through pixels is effectively corrected, so that the original appearance of the document is preserved. We evaluate the performance of the proposed method on the images of a popular database of ancient documents, and the results validate the performance of the proposed method compared to the state of the art. View Full-Text
Keywords: ancient document restoration; image inpainting; bleed-through removal; sparse representation ancient document restoration; image inpainting; bleed-through removal; sparse representation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Printed Edition Available!
A printed edition of this Special Issue is available here.

Share & Cite This Article

MDPI and ACS Style

Hanif, M.; Tonazzini, A.; Savino, P.; Salerno, E. Non-Local Sparse Image Inpainting for Document Bleed-Through Removal. J. Imaging 2018, 4, 68.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top