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Journal of Electronic Imaging

Compound L0 regularization method for image blind motion deblurring
Author(s): Qiaohong Liu; Liping Sun; Zeguo Shao
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Paper 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.

Paper Details

Date Published: 20 September 2016
PDF: 15 pages
J. Electron. Imag. 25(5) 053013 doi: 10.1117/1.JEI.25.5.053013
Published in: Journal of Electronic Imaging Volume 25, Issue 5
Show Author Affiliations
Qiaohong Liu, Shanghai Univ. of Medicine and Health Sciences (China)
Liping Sun, Shanghai Univ. of Medicine and Health Sciences (China)
Zeguo Shao, Shanghai Univ. of Medicine and Health Sciences (China)


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