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Choice of Parameters in the Weighted Nuclear Norm Method for Image Denoising

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We consider the choice of image denoising parameters in an algorithm based on singular decomposition and minimization of the weighted nuclear norm. An automated parameter-choosing method is proposed that analyzes the structures on a difference image between the original noisy image and the denoised result and performs a quantitative assessment of the structures — computes the mutual information coefficient. We also analyze the choice of optimal parameters for different noise levels using a database of photographic images with normally distributed simulated noise. The denoising results are compared for the optimal choice of parameters and the choice of parameters by the mutual information coefficient, and also with denoising by a Peron–Malik diffusion algorithm.

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Authors and Affiliations

  1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia

    O. S. Volodina, A.V. Nasonov & A. S. Krylov

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  1. O. S. Volodina
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  2. A.V. Nasonov
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  3. A. S. Krylov
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Correspondence to O. S. Volodina.

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Translated from Prikladnaya Matematika i Informatika, No. 63, 2019, pp. 105–114.

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Volodina, O.S., Nasonov, A. & Krylov, A.S. Choice of Parameters in the Weighted Nuclear Norm Method for Image Denoising. Comput Math Model 31, 402–409 (2020). https://doi.org/10.1007/s10598-020-09500-z

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  • DOI: https://doi.org/10.1007/s10598-020-09500-z

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