Blind image blurring by Gaussian filtering extreme channels prior
Pages 550 - 555
Abstract
Previous extreme channels prior deblurring methods still cannot solve noise and avoid ringing artifacts in restored image problems well. In order to solve these caused, we propose a Gaussian filtering extreme channels prior (GFECP) to plug the Gaussian filtering into extreme channels prior work architecture for effective blind image deblurring. First, we computed image structure based on the Gaussian filtering model and extreme channels prior. Second, the half quadratic splitting technique is used to solve the non-convex problem of the model and estimate the clear image. Finally, we use an iterative multi-scale blind deconvolution method as regularization to restore the blur kernel. Experimental results clearly demonstrate that the proposed method outperforms state-of-the-art methods in terms of robustness, subjective visual effects and objective evaluation indexes.
References
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Index Terms
- Blind image blurring by Gaussian filtering extreme channels prior
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October 2021
1723 pages
ISBN:9781450384322
DOI:10.1145/3501409
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Association for Computing Machinery
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Published: 31 December 2021
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EITCE 2021
EITCE 2021: 2021 5th International Conference on Electronic Information Technology and Computer Engineering
October 22 - 24, 2021
Xiamen, China
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EITCE '21 Paper Acceptance Rate 294 of 531 submissions, 55%;
Overall Acceptance Rate 508 of 972 submissions, 52%
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