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Text Image Deblurring Using Text-Specific Properties

  • Hojin Cho
  • Jue Wang
  • Seungyong Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7576)

Abstract

State-of-the-art blind image deconvolution approaches have difficulties when dealing with text images, since they rely on natural image statistics which do not respect the special properties of text images. On the other hand, previous document image restoring systems and the recently proposed black-and-white document image deblurring method [1] are limited, and cannot handle large motion blurs and complex background. We propose a novel text image deblurring method which takes into account the specific properties of text images. Our method extends the commonly used optimization framework for image deblurring to allow domain-specific properties to be incorporated in the optimization process. Experimental results show that our method can generate higher quality deblurring results on text images than previous approaches.

Keywords

Text Image Latent Image Document Image Kernel Estimation Text Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hojin Cho
    • 1
  • Jue Wang
    • 2
  • Seungyong Lee
    • 1
  1. 1.Pohang University of Science and Technology (POSTECH)Korea
  2. 2.AdobeUSA

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