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Proceedings Paper

Robustifying blind image deblurring methods by simple filters
Author(s): Yan Liu; Xiangrong Zeng; Qizi Huangpeng; Jun Fan; Jinglun Zhou; Jing Feng
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Paper Abstract

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

Paper Details

Date Published: 11 July 2016
PDF: 5 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110O (11 July 2016); doi: 10.1117/12.2242865
Show Author Affiliations
Yan Liu, National Univ. of Defense Technology (China)
Xiangrong Zeng, National Univ. of Defense Technology (China)
Qizi Huangpeng, National Univ. of Defense Technology (China)
Jun Fan, National Univ. of Defense Technology (China)
Jinglun Zhou, National Univ. of Defense Technology (China)
Jing Feng, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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