23 June 2015 Mean curvature regularization-based Poisson image restoration
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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.
© 2015 SPIE and IS&T
Fuquan Ren, Fuquan Ren, Tianshuang Qiu, Tianshuang Qiu, Hui Liu, Hui Liu, } "Mean curvature regularization-based Poisson image restoration," Journal of Electronic Imaging 24(3), 033025 (23 June 2015). https://doi.org/10.1117/1.JEI.24.3.033025 . Submission:
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