Enhancement of historical printed document images by combining Total Variation regularization and Non-local Means filtering

Authors:
Laurence Likforman-Sulem;Jérôme Darbon;Elisa H. Barney Smith
Affiliations:
Telecom ParisTech, Signal and Image Processing Department Paris, France;Mathematics Department, UCLA, Los Angeles, California, USA and CMLA, ENS Cachan, CNRS, PRES UniverSud, France;Boise State University, Electrical and Computer Engineering Department, Boise, Idaho, USA
Venue:
Image and Vision Computing
Year:
2011

Citing 24
Cited 2

Minimum error thresholding

Pattern Recognition
Scale-Space and Edge Detection Using Anisotropic Diffusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms

Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Characterization of image degradation caused by scanning

Pattern Recognition Letters
Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures

Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures
Correcting broken characters in the recognition of historical printed documents

Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Binarization of Low Quality Text Using a Markov Random Field Model

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
An Algorithm for Total Variation Minimization and Applications

Journal of Mathematical Imaging and Vision
Analysis and recognition of highly degraded printed characters

International Journal on Document Analysis and Recognition
Independent component analysis for document restoration

International Journal on Document Analysis and Recognition
A new approach for image enhancement applied to low-contrast-low-illumination IC and document images

Pattern Recognition Letters
Input sensitive thresholding for ancient Hebrew manuscript

Pattern Recognition Letters
Image Restoration with Discrete Constrained Total Variation Part I: Fast and Exact Optimization

Journal of Mathematical Imaging and Vision
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)

Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Adaptive degraded document image binarization

Pattern Recognition
An Overview of the Tesseract OCR Engine

ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
OCR Accuracy Improvement through a PDE-Based Approach

ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
An optical character recognition approach to qualifying thresholding algorithms

Proceedings of the eighth ACM symposium on Document engineering
Morphological preprocessing method to thresholding degraded word images

Pattern Recognition Letters
A Unified Framework Based on the Level Set Approach for Segmentation of Unconstrained Double-Sided Document Images Suffering from Bleed-Through

ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Registration and Enhancement of Double-Sided Degraded Manuscripts Acquired in Multispectral Modality

ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Pre-Processing of Degraded Printed Documents by Non-local Means and Total Variation

ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
ICDAR 2009 Document Image Binarization Contest (DIBCO 2009)

ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
A generalized Gaussian image model for edge-preserving MAP estimation

IEEE Transactions on Image Processing

Image reconstruction with locally adaptive sparsity and nonlocal robust regularization

Image Communication
Enhancing dynamic videos for surveillance and robotic applications: The robust bilateral and temporal filter

Image Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a novel method for document enhancement which combines two recent powerful noise-reduction steps. The first step is based on the Total Variation framework. It flattens background grey-levels and produces an intermediate image where background noise is considerably reduced. This image is used as a mask to produce an image with a cleaner background while keeping character details. The second step is applied to the cleaner image and consists of a filter based on Non-local Means: character edges are smoothed by searching for similar patch images in pixel neighborhoods. The document images to be enhanced are real historical printed documents from several periods which include several defects in their background and on character edges. These defects result from scanning, paper aging and bleed-through. The proposed method enhances document images by combining the Total Variation and the Non-local Means techniques in order to improve OCR recognition. The method is shown to be more powerful than when these techniques are used alone and than other enhancement methods.