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论文类型：期刊论文

发表时间：2016-03-01

发表刊物：JOURNAL OF ELECTRONIC IMAGING

收录刊物：SCIE、EI、Scopus

卷号：25

期号：2

ISSN号：1017-9909

关键字：image deblurring; low illumination; light streaks; kernel estimation; kernel shape; kernel sparsity

摘要：Deblurring images captured from low-illumination conditions is a challenging task, because these images contain few useful structures for kernel estimation. However, these images usually contain some light streaks, which are beneficial for estimating the blur kernel. One of our key observations is that these light streaks can provide a good initial value for a nonconvex problem in kernel estimation. The other one is that they record the track of the blur kernel at the moment when images are taken. Therefore, we propose a new prior for kernel estimation based on light streaks in this paper. Moreover, in order to ensure the shape of the blur kernel to be similar to that of light streaks during the updating, a new method is proposed to refine the shape of light streaks. With the help of the refined shape, our kernel estimation process does not require heuristic coarse-to-fine strategy, which is widely used in image deblurring methods. Quantitative experimental results show the effectiveness of the proposed method. In addition, we also demonstrate that the proposed method can be applied to the existing deblurring methods to achieve better performance. (C) 2016 SPIE and IS&T