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Open AccessArticle

Image Restoration Using Fixed-Point-Like Methods for New TVL1 Variational Problems

Department of Mathematics, College of Natural Sciences, Chungbuk National University, Cheongju 28644, Korea
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Electronics 2020, 9(5), 735; https://doi.org/10.3390/electronics9050735
Received: 29 February 2020 / Revised: 25 April 2020 / Accepted: 27 April 2020 / Published: 29 April 2020
(This article belongs to the Section Computer Science & Engineering)
In this paper, we first propose two TVL1 variational problems for restoring images degraded by blurring and impulse noise, and then we propose two fixed-point-like methods, using proximal operators, for solving the new proposed TVL1 problems. Numerical experiments for several test images blurred by Gaussian kernel and corrupted by salt-and-pepper impulse noise are provided to demonstrate the efficiency and reliability of the proposed fixed-point-like methods. Numerical results show that two fixed-point-like methods for solving the new TVL1 variational problems perform very well in both PSNR (Peak signal-to-noise ratio) values and CPU time as compared with the fixed-point-like methods for solving two existing TVL1 variational problems. View Full-Text
Keywords: TVL1 problems; fixed-point-like method; image restoration; impulse noise; proximal operator TVL1 problems; fixed-point-like method; image restoration; impulse noise; proximal operator
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Yun, J.H.; Lim, H.J. Image Restoration Using Fixed-Point-Like Methods for New TVL1 Variational Problems. Electronics 2020, 9, 735.

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