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Mean curvature regularization-based Poisson image restoration

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First Author:Ren, Fuquan

Correspondence Author:Ren, FQ (reprint author), Dalian Univ Technol, Sch Informat & Commun Engn, 2 Linggong Rd, Dalian 116023, Peoples R China.

Co-author:Qiu, Tianshuang,Liu, Hui

Date of Publication:2015-05-01

Journal:JOURNAL OF ELECTRONIC IMAGING

Included Journals:SCIE、EI、Scopus

Volume:24

Issue:3

ISSN No.:1017-9909

Key Words:Poisson noise; image deblurring; mean curvature regularization; augmented Lagrange multiplier

Abstract: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

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