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Blind deconvolution for single noisy and blurry image using alternating maximum a posteriori estimation with low rank prior
Sun SJ(孙世杰); Zhao HC(赵怀慈); Lv JF(吕进锋); Hao MG(郝明国); Li B(李波)
Department光电信息技术研究室
Conference Name2016 16th International Symposium on Communications and Information Technologies (ISCIT)
Conference DateSeptember 26-28, 2016
Conference PlaceQingdao, China
Source Publication2016 16th International Symposium on Communications and Information Technologies, ISCIT 2016
PublisherIEEE
Publication PlaceNew York
2016
Pages175-181
Indexed ByEI ; CPCI(ISTP)
EI Accession number20165203181067
WOS IDWOS:000391872600037
Contribution Rank1
ISBN978-1-5090-4100-8
KeywordMap Blind Deconvolution Low Rank Prior Noise
Abstract

The 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 task is severely ill-posed and even more challenging especially in the condition that the noise in the input image cannot be negligible. In this paper, the main problem we focus 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. When estimating the intermediate latent image, low rank prior is used as the constraint that is used for noise suppression of the restored image. 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. Extensive experiments show the superiority of the proposed method over state-of-the-art techniques, both qualitatively and quantitatively.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/19760
Collection光电信息技术研究室
Corresponding AuthorSun SJ(孙世杰)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Science, Beijing, China
3.Key Laboratory of Optical-Electronics Information Processing, Chinese Academy of Sciences, Shenyang, China
4.Key Laboratory of Image Understanding and Computer Vision, Shenyang, China
5.College of Information, Shenyang Institute of Engineering, Shenyang, China
Recommended Citation
GB/T 7714
Sun SJ,Zhao HC,Lv JF,et al. Blind deconvolution for single noisy and blurry image using alternating maximum a posteriori estimation with low rank prior[C]. New York:IEEE,2016:175-181.
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