Text Image Deblurring Using Text-specific Properties

Hojin Cho, Jue Wang, Seungyong Lee

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-andwhite
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.