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 to be 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. https://doi.org/10.4208/jcm.2503-m2024-0010