An Adaptive Algorithm for L1-Fidelity Color Image Restoration

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Abstract

In this paper, we propose an adaptive algorithm for L1-fidelity color image restoration by using saturation-value total variation. The main contribution of this paper is to employ the generalized cross validation method efficiently and automatically to estimate the regularization parameter in a saturation-value total variation plus L1-fidelity color image restoration model. We consider Poisson noise and mixed noise in this paper, and the experimental results show that the visual quality and the SSIM/PSNR/SAM values of the restored images by using the proposed algorithm are competitive with other tested existing methods, which makes the proposed algorithm comparable both quantitatively and qualitatively.

Author Biographies

  • Wei Wang

    School of Mathematical Sciences, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai 200092, China

  • Chengyun Yang

    School of Mathematical Sciences, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai 200092, China

  • Qifan Song

    School of Mathematical Sciences, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai 200092, China

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DOI

10.4208/jcm.2503-m2024-0010

How to Cite

An Adaptive Algorithm for L1-Fidelity Color Image Restoration. (2025). Journal of Computational Mathematics, 44(3), 779–793. https://doi.org/10.4208/jcm.2503-m2024-0010