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Journal of Electronic Imaging

Mean curvature regularization-based Poisson image restoration
Author(s): Fuquan Ren; Tianshuang Qiu; Hui Liu
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Paper 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.

Paper Details

Date Published: 23 June 2015
PDF: 15 pages
J. Electron. Imaging. 24(3) 033025 doi: 10.1117/1.JEI.24.3.033025
Published in: Journal of Electronic Imaging Volume 24, Issue 3
Show Author Affiliations
Fuquan Ren, Dalian Univ. of Technology (China)
Tianshuang Qiu, Dalian Univ. of Technology (China)
Hui Liu, Dalian Univ. of Technology (China)


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