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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)
作者部门光电信息技术研究室
会议名称2016 16th International Symposium on Communications and Information Technologies (ISCIT)
会议日期September 26-28, 2016
会议地点Qingdao, China
会议录名称2016 16th International Symposium on Communications and Information Technologies, ISCIT 2016
出版者IEEE
出版地New York
2016
页码175-181
收录类别EI ; CPCI(ISTP)
EI收录号20165203181067
WOS记录号WOS:000391872600037
产权排序1
ISBN号978-1-5090-4100-8
关键词Map Blind Deconvolution Low Rank Prior Noise
摘要

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.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/19760
专题光电信息技术研究室
通讯作者Sun SJ(孙世杰)
作者单位1.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
推荐引用方式
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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