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An adaptive parameter estimation for guided filter based image deconvolution
Yang, H.; Z. B. Zhang and Y. J. Guan
2017
Source PublicationSignal Processing
Volume138
AbstractImage deconvolution is still to be a challenging ill-posed problem for recovering a clear image from a given blurry image, when the point spread function is known. Although competitive deconvolution methods are numerically impressive and approach theoretical limits, they are becoming more complex, making analysis, and implementation difficult. Furthermore, accurate estimation of the regularization parameter is not easy for successfully solving image deconvolution problems. In this paper, we develop an effective approach for image restoration based on one explicit image filter - guided filter. By applying the de couple of denoising and deblurring techniques to the deconvolution model, we reduce the optimization complexity and achieve a simple but effective algorithm to automatically compute the parameter in each iteration, which is based on Morozov's discrepancy principle. Experiments manifest that our algorithm is effective on finding a good regularization parameter, and the proposed algorithm outperforms many competitive methods in both ISNR and visual quality. (C) 2017 Elsevier B.V. All rights reserved.
Indexed Bysci ; ei
Language英语
Document Type期刊论文
Identifierhttp://ir.ciomp.ac.cn/handle/181722/59374
Collection中科院长春光机所知识产出
Recommended Citation
GB/T 7714
Yang, H.,Z. B. Zhang and Y. J. Guan. An adaptive parameter estimation for guided filter based image deconvolution[J]. Signal Processing,2017,138.
APA Yang, H.,&Z. B. Zhang and Y. J. Guan.(2017).An adaptive parameter estimation for guided filter based image deconvolution.Signal Processing,138.
MLA Yang, H.,et al."An adaptive parameter estimation for guided filter based image deconvolution".Signal Processing 138(2017).
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