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Blind restoration of camera shake blurred image based on L0 sparse priors
Qiu, X. and M. Dai
2017
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
卷号25期号:9
摘要An improved regularization blind restoration method based on L0 sparse prior was proposed to overcome the image blue from camera shake. A new optimization mode on the basis of inherent property which the gradient distribution of the blurred image is denser than that of the clear image and the sparse of the dark channel is relatively smaller. Aiming at the highly non-convex of L0 norm and nonlinear minimization problem in the dark channel sparse optimization process, an approximate linear map matrix based on look-up tables was proposed, and the linearized L0 minimization problem was solved by half-quadratic splitting methods. Finally, the fast Fourier transform was used to do iterative operation alternately for the fuzzy kernel and the clear image in frequency domain to obtain the restored image. Through experiments on several different types of blurred images, the results show that average gray level gradient is up to 11.411, the image entropy is up to 7.304, and it only takes 8.07s to process 365285 images. The improved regularization algorithm effectively suppresses the ringing effect near the edge of the image, retains the integrity of clear details, improves the speed of operation significantly. The algorithm is suitable for all kinds of image restoration. 2017, Science Press. All right reserved.
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语种中文
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/59164
专题中科院长春光机所知识产出
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Qiu, X. and M. Dai. Blind restoration of camera shake blurred image based on L0 sparse priors[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2017,25(9).
APA Qiu, X. and M. Dai.(2017).Blind restoration of camera shake blurred image based on L0 sparse priors.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,25(9).
MLA Qiu, X. and M. Dai."Blind restoration of camera shake blurred image based on L0 sparse priors".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 25.9(2017).
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