@inproceedings{a62c45c610f24a438fd932fa7e7d9d74,
title = "An effective document image deblurring algorithm",
abstract = "Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method.",
author = "Xiaogang Chen and Xiangjian He and Jie Yang and Qiang Wu",
year = "2011",
doi = "10.1109/CVPR.2011.5995568",
language = "English",
isbn = "9781457703942",
series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE Computer Society",
pages = "369--376",
booktitle = "2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011",
address = "United States",
}