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Multiparent Fractal Image Coding-Based Methods For Salt-And-Pepper Noise Removal

Author

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  • WEIJIE LIANG

    (Shenzhen Key Laboratory of Advanced Machine Learning and Applications, School of Mathematical Sciences, Shenzhen University, Shenzhen, 518060, P. R. China2National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518055, P. R. China3The Pazhou Lab, Guangzhou 510335, P. R. China)

  • XIAOYI LI

    (Shenzhen Key Laboratory of Advanced Machine Learning and Applications, School of Mathematical Sciences, Shenzhen University, Shenzhen, 518060, P. R. China2National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518055, P. R. China3The Pazhou Lab, Guangzhou 510335, P. R. China)

  • ZHIHUI TU

    (Shenzhen Key Laboratory of Advanced Machine Learning and Applications, School of Mathematical Sciences, Shenzhen University, Shenzhen, 518060, P. R. China2National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518055, P. R. China3The Pazhou Lab, Guangzhou 510335, P. R. China)

  • JIAN LU

    (Shenzhen Key Laboratory of Advanced Machine Learning and Applications, School of Mathematical Sciences, Shenzhen University, Shenzhen, 518060, P. R. China2National Center for Applied Mathematics Shenzhen (NCAMS), Shenzhen 518055, P. R. China3The Pazhou Lab, Guangzhou 510335, P. R. China)

Abstract

Salt-and-pepper noise consists of outlier pixel values which significantly impair image structure and quality. Multiparent fractal image coding (MFIC) methods substantially exploit image redundancy by utilizing multiple domain blocks to approximate the range block, partially compensating for the information loss caused by noise. Motivated by this, we propose two novel image restoration methods based on MFIC to remove salt-and-pepper noise. The first method integrates Huber M-estimation into MFIC, resulting in an improved anti-salt-and-pepper noise robust fractal coding approach. The second method incorporates MFIC into a total variation (TV) regularization model, including a data fidelity term, an MFIC term and a TV regularization term. An alternative iterative method based on proximity operator is developed to effectively solve the proposed model. Experimental results demonstrate that these two proposed approaches achieve significantly enhanced performance compared to traditional fractal coding methods.

Suggested Citation

  • Weijie Liang & Xiaoyi Li & Zhihui Tu & Jian Lu, 2024. "Multiparent Fractal Image Coding-Based Methods For Salt-And-Pepper Noise Removal," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 32(01), pages 1-15.
    • Handle: RePEc:wsi:fracta:v:32:y:2024:i:01:n:s0218348x24500129
    DOI: 10.1142/S0218348X24500129
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