By Topic

Super-Resolution of Text Images Using Edge-Directed Tangent Field

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Banerjee, J. ; Centre for Visual Inf. Technol., IIIT, Hyderabad ; Jawahar, C.V.

This paper presents an edge-directed super-resolution algorithm for document images without using any training set. This technique creates an image with smooth regions in both the foreground and the background, while allowing sharp discontinuities across and smoothness along the edges. Our method preserves sharp corners in text images by using the local edge direction, which is computed first by evaluating the gradient field and then taking its tangent. Super-resolution of document images is characterized by bimodality, smoothness along the edges as well as subsampling consistency. These characteristics are enforced in a Markov random field (MRF) framework by defining an appropriate energy function. In our method, subsampling of super-resolution image will return the original low-resolution one, proving the correctness of the method. The super-resolution image, is generated by iteratively reducing this energy function. Experimental results on a variety of input images, demonstrate the effectiveness of our method for document image super-resolution.

Published in:

Document Analysis Systems, 2008. DAS '08. The Eighth IAPR International Workshop on

Date of Conference:

16-19 Sept. 2008