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Adaptive Parameter Selection for Preserving Edges Based on EPLL

Year:    2021

Author:    Ze Qin, Xiulan Sheng

Journal of Information and Computing Science, Vol. 16 (2021), Iss. 2 : pp. 98–107

Abstract

Though image denoising has experienced rapid development, there remain problems to be solved such as preserving the edge and meaningful details in image denoising. In this paper, we focus on this hot issue. Considering the parameter in original method is a constant, we introduce a new adaptive parameter selection based on EPLL (Expected Patch Log Likelihood) by the use of image gradient and the local variance, which varies with different regions of the image. What’s more, for solving staircase effect which common in anisotropic diffusion models, we add a gradient fidelity term to release it. The experiment shows that our proposed method proves the effectiveness not only in vision but also on quantitative evaluation.

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2024-JICS-22367

Journal of Information and Computing Science, Vol. 16 (2021), Iss. 2 : pp. 98–107

Published online:    2021-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:    Image denoising adaptive parameter expected patch log likelihood edges.

Author Details

Ze Qin

Xiulan Sheng