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Bilateral signal variance estimation for wavelet-domain image denoising

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Abstract

The estimation of the signal variance is a critical challenge in wavelet-domain minimum mean square error (MMSE) based image denoising. In contrast to the conventional approaches that treat the neighboring wavelet coefficients equally to estimate the signal variance at each coefficient position, here an adaptive approach is proposed that utilizes a bilateral statistical scheme adaptively adjusting the contributions of neighboring wavelet coefficients to provide an accurate estimation of the signal variance. Experimental results are presented to demonstrate the superior performance of the proposed approach.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China

    JingLun Shi

  2. School of Mathematics and Statistics, Zaozhuang University, Zaozhuang, 277160, China

    ZhenYu Liu

  3. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China

    Jing Tian

Authors
  1. JingLun Shi
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  2. ZhenYu Liu
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  3. Jing Tian
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Correspondence to JingLun Shi.

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Shi, J., Liu, Z. & Tian, J. Bilateral signal variance estimation for wavelet-domain image denoising. Sci. China Inf. Sci. 56, 1–6 (2013). https://doi.org/10.1007/s11432-012-4762-9

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  • DOI: https://doi.org/10.1007/s11432-012-4762-9

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