Robustifying blind image deblurring methods by simple filters

Yan Liu; Xiangrong Zeng; Qizi Huangpeng; Jun Fan; Jinglun Zhou; Jing Feng

doi:10.1117/12.2242865

11 July 2016 Robustifying blind image deblurring methods by simple filters

Yan Liu, Xiangrong Zeng, Qizi Huangpeng, Jun Fan, Jinglun Zhou, Jing Feng

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.

Citation Download Citation

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

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