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Blind motion image deblurring using nonconvex higher-order total variation model

[+] Author Affiliations
Weihong Li, Rui Chen, Weiguo Gong

Chongqing University, College of Optoelectronic Enginerring, Room 1303, Main Building, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China

Shangwen Xu

Zhongxing Telecommunication Equipment Corporation, No. 55, Hi-tech Road South, Shenzhen 518057, China

J. Electron. Imaging. 25(5), 053033 (Oct 19, 2016). doi:10.1117/1.JEI.25.5.053033
History: Received May 27, 2016; Accepted September 20, 2016
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Abstract.  We propose a nonconvex higher-order total variation (TV) method for blind motion image deblurring. First, we introduce a nonconvex higher-order TV differential operator to define a new model of the blind motion image deblurring, which can effectively eliminate the staircase effect of the deblurred image; meanwhile, we employ an image sparse prior to improve the edge recovery quality. Second, to improve the accuracy of the estimated motion blur kernel, we use L1 norm and H1 norm as the blur kernel regularization term, considering the sparsity and smoothing of the motion blur kernel. Third, because it is difficult to solve the numerically computational complexity problem of the proposed model owing to the intrinsic nonconvexity, we propose a binary iterative strategy, which incorporates a reweighted minimization approximating scheme in the outer iteration, and a split Bregman algorithm in the inner iteration. And we also discuss the convergence of the proposed binary iterative strategy. Last, we conduct extensive experiments on both synthetic and real-world degraded images. The results demonstrate that the proposed method outperforms the previous representative methods in both quality of visual perception and quantitative measurement.

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Citation

Weihong Li ; Rui Chen ; Shangwen Xu and Weiguo Gong
"Blind motion image deblurring using nonconvex higher-order total variation model", J. Electron. Imaging. 25(5), 053033 (Oct 19, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.5.053033


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