Adaptive edge-preserving denoising algorithm based on anisotropic diffusion model

Xianjun Han; Xue Wang; Huabin Wang; Xuejun Li; Yibing Li

doi:10.1117/12.2626708

20 December 2021 Adaptive edge-preserving denoising algorithm based on anisotropic diffusion model

Xianjun Han, Xue Wang, Huabin Wang, Xuejun Li, Yibing Li

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 1215502 (2021) https://doi.org/10.1117/12.2626708
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

Digital image quality is disturbed by noise to some extent. Researchers proposed a series of wavelet transform, non-local mean, and partial differential equation denoising algorithms to obtain high-quality images for subsequent research. Removing noise and preserving the edges and details of the image has attracted wide publicity. Methods based on anisotropic diffusion models have recently gained popularity, but these lead to over-smooth the image details. In this paper, we propose an improved denoising algorithm based on the anisotropic diffusion model. Our method further modifies the diffusion coefficient of the denoising model based on fractional differential operator and Gauss curvature (FDOGC). We use the edge-preserving characteristic of bilateral filtering to recover the image texture and adjust the diffusion coefficient given the characteristics of local variance. To balance the performance of denoising and edge-preserving, we add a regularization term to the diffusion model. We conduct ablation studies to verify the effectiveness of the innovation points. Our method can adjust the counterpoise between noise removal and edge preservation. Extensive experiments on public standard datasets indicate the superiority of our algorithm, in terms of not only quantitative and qualitative evaluation but also better visual effects.

Citation Download Citation

Xianjun Han, Xue Wang, Huabin Wang, Xuejun Li, and Yibing Li "Adaptive edge-preserving denoising algorithm based on anisotropic diffusion model", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 1215502 (20 December 2021); https://doi.org/10.1117/12.2626708

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KEYWORDS

Diffusion

Denoising

Image filtering

Image processing

Anisotropic diffusion

Gaussian filters

Image denoising

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