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论文类型： 期刊论文

发表时间： 2015-05-01

发表刊物： JOURNAL OF ELECTRONIC IMAGING

收录刊物： SCIE、EI、Scopus

卷号： 24

期号： 3

ISSN号： 1017-9909

关键字： Poisson noise; image deblurring; mean curvature regularization; augmented Lagrange multiplier

摘要： The restoration of blurred images corrupted by Poisson noise is an important task in various applications such as medical imaging, microscopy imaging, and so on. We focus on mean curvature-based regularization to address the Poisson noise image restoration problem. Furthermore, we derive a numerical algorithm based on the augmented Lagrange multiplier method with a splitting technique. In order to simultaneously demonstrate the effectiveness of the proposed method for Poisson noise removal with deblurring, we conduct systematic experiments on both nature images and biological images. Experimental results show that the proposed approach can produce higher quality results and more natural images compared to some state-of-the-art variational algorithms recently developed. (C) 2015 SPIE and IS&T