Abstract
An overview of additive noise reduction algorithms using nonlinear second-order partial differential equations (PDEs) is provided here. First, the state-of-the-art anisotropic diffusion models that are used for image restoration are described here. The second-order PDE-based denoising approaches using variational schemes are addressed next. Our most important contributions in these image processing fields are also discussed in this work and method comparison examples are provided, too.
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Acknowledgement
This research presented here was supported from the project PN-III-P4-ID-PCE-2016-0011, which is financed by UEFISCDI Romania.
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Barbu, T. (2021). A Survey on Nonlinear Second-Order Diffusion-Based Techniques for Additive Denoising. In: Balas, V., Jain, L., Balas, M., Shahbazova, S. (eds) Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, vol 1221. Springer, Cham. https://doi.org/10.1007/978-3-030-51992-6_15
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