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Compound L0 regularization method for image blind motion deblurring

[+] Author Affiliations
Qiaohong Liu, Liping Sun, Zeguo Shao

Shanghai University of Medicine and Health Sciences, School of Health Information Technology and Management, No. 279, Zhouzhu Road, Shanghai 201318, China

J. Electron. Imaging. 25(5), 053013 (Sep 20, 2016). doi:10.1117/1.JEI.25.5.053013
History: Received April 17, 2016; Accepted August 26, 2016
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Abstract.  Blind image deblurring is one of the challenging problems in image processing and computer vision. The main purpose of blind image deblurring is to estimate the correct blur kernel and restore the latent image with edge-preservation, details-protection, and ringing suppression. In order to achieve ideal results, an innovative compound L0-regularized model is proposed to estimate the blur kernel by regularizing the sparsity property of natural images and two characteristics of blur kernel, such as continuity and sparsity. In the alternating direction framework, the split Bregman algorithm and half-quadratic splitting rule are alternatively employed to optimize the proposed kernel estimation model. Finally, a nonblind restoration method with ringing suppression is developed to obtain the ultimate latent image. Extensive experiments demonstrate the efficiency and viability of the proposed method compared with some state-of-the-art blind deblurring methods.

© 2016 SPIE and IS&T

Citation

Qiaohong Liu ; Liping Sun and Zeguo Shao
"Compound L0 regularization method for image blind motion deblurring", J. Electron. Imaging. 25(5), 053013 (Sep 20, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.5.053013


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