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论文类型：期刊论文

发表时间：2013-01-01

发表刊物：IEEE Signal Processing Letters

收录刊物：EI、Scopus

卷号：20

期号：9

页面范围：841-844

摘要：Blind image deblurring is a challenging problem in computer vision and image processing. In this paper, we propose a new ?0-regularized approach to estimate a blur kernel from a single blurred image by regularizing the sparsity property of natural images. Furthermore, by introducing an adaptive structure map in the deblurring process, our method is able to restore useful salient edges for kernel estimation. Finally, we propose an efficient algorithm which can solve the proposed model efficiently. Extensive experiments compared with state-of-the-art blind deblurring methods demonstrate the effectiveness of the proposed method. ? 1994-2012 IEEE.