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Alternative TitleBlind Deconvolution for Noisy and Blurry Images Using Low Rank Prior
孙士洁; 赵怀慈; 李波; 郝明国; 吕进锋
Source Publication电子与信息学报
Indexed ByEI ; CSCD
EI Accession number20174404321147
Contribution Rank1
Funding Organization辽宁省教育厅科研项目(L2015368)
Keyword盲去卷积 最大后验估计 噪声模糊图像 低秩先验
Other AbstractThe purpose of single image blind deconvolution is to estimate the unknown blur kernel from a single observed blurred image and recover the original sharp image. Such a task is severely ill-posed and even more challenging especially in the condition that the noise in the input image can not be negligible. In this paper, the main problem this study focuses on is how to effectively apply low rank prior to blind deconvolution. A single noisy and blurry image blind deconvolution algorithm is proposed, using alternating Maximum A Posteriori (MAP) estimation combined with low rank prior. First, when estimating the intermediate latent image, low rank prior is used as the constraint that is used for noise suppression of the restored image. Then the denoised intermediate latent image in turn leads to higher quality blur kernel estimation. These two operations are iterated in this manner to arrive at reliable blur kernel estimation. Finally, the non-blind deconvolution method is chosen to be used with sparse prior knowledge to achieve the final latent image restoration. Extensive experiments manifest the superiority of the proposed method over state-of-the-art techniques, both qualitatively and quantitatively.
Citation statistics
Cited Times:4[CSCD]   [CSCD Record]
Document Type期刊论文
Corresponding Author孙士洁
Recommended Citation
GB/T 7714
孙士洁,赵怀慈,李波,等. 利用低秩先验的噪声模糊图像盲去卷积[J]. 电子与信息学报,2017,39(8):1919-1926.
APA 孙士洁,赵怀慈,李波,郝明国,&吕进锋.(2017).利用低秩先验的噪声模糊图像盲去卷积.电子与信息学报,39(8),1919-1926.
MLA 孙士洁,et al."利用低秩先验的噪声模糊图像盲去卷积".电子与信息学报 39.8(2017):1919-1926.
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