11 July 2016 Robustifying blind image deblurring methods by simple filters
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Proceedings Volume 10011, First International Workshop on Pattern Recognition; 100110O (2016) https://doi.org/10.1117/12.2242865
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan
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.
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Yan Liu, Xiangrong Zeng, Qizi Huangpeng, Jun Fan, Jinglun Zhou, Jing Feng, "Robustifying blind image deblurring methods by simple filters", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110O (11 July 2016); doi: 10.1117/12.2242865; https://doi.org/10.1117/12.2242865
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