20 May 2024 Image denoising model using adaptive regularization parameter based on structure tensor
Yuhang Zhao, Ping Zhao
Author Affiliations +
Abstract

The denoising method based on partial differential equation (PDE) has been proven to be a calculable method and used widely, but it is not good at protecting image detail information and results in staircase effect. To improve the above shortcomings, a PDE image denoising model based on a structure tensor matrix is proposed and explained in this work. Combining two different regular terms and adjusting their proportion, the proposed model uses the eigenvalues of the structure tensor to take the norm parameter value of the second regular term. The experiment results show that the proposed model introduced structure tensor can protect details and suppress the staircase effect effectively, thus obtaining satisfying denoising results.

© 2024 SPIE and IS&T
Yuhang Zhao and Ping Zhao "Image denoising model using adaptive regularization parameter based on structure tensor," Journal of Electronic Imaging 33(3), 033022 (20 May 2024). https://doi.org/10.1117/1.JEI.33.3.033022
Received: 8 June 2023; Accepted: 7 May 2024; Published: 20 May 2024
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KEYWORDS
Denoising

Image denoising

Matrices

Cameras

Diffusion

Eye models

Mathematical modeling

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