Robust image deblurring using hyper Laplacian model
Xu Yuquan; Hu Xiyuan; Peng Silong
2013
会议名称11th Asian Conference on Computer Vision ACCV 2012
页码pp 49-60
会议日期2012/11/5-2012/11/6
会议地点韩国Daejeon Korea Republic of Korea
摘要In recent years many image deblurring algorithms have been proposed most of which assume the noise in the deblurring process satisfies the Gaussian distribution. However it is often unavoidable in practice both in nonblind and blind image deblurring due to the error on the input kernel and the outliers in the blurry image. Without proper handing these outliers the recovered image estimated by previous methods will suffer severe artifacts. In this paper we mainly deal with two kinds of non-Gaussian noise in the image deblurring process inaccurate kernel and compressed blurry image and find that handling the noise as Laplacian distribution can get more robust result in these cases. Based on this point the new non-blind and blind image deblurring algorithms are proposed to restore the clear image. To get more robust deblurred result we also use 8 direction gradients of the image to estimate the blur kernel. The new minimization problem can be efficiently solved by the Iteratively Reweighted Least Squares(IRLS) and the experimental results on both synthesized and real-world images show the efficiency and robustness of our algorithm.
关键词
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12872
专题智能制造技术与系统研究中心_多维数据分析
通讯作者Xu Yuquan
推荐引用方式
GB/T 7714
Xu Yuquan,Hu Xiyuan,Peng Silong. Robust image deblurring using hyper Laplacian model[C],2013:pp 49-60.
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