TY - JOUR
T1 - Adaptive Parameter Selection for Preserving Edges Based on EPLL
AU - Qin , Ze
AU - Sheng , Xiulan
JO - Journal of Information and Computing Science
VL - 2
SP - 098
EP - 107
PY - 2024
DA - 2024/01
SN - 16
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22367.html
KW - Image denoising, adaptive parameter, expected patch log likelihood, edges.
AB - <p style="text-align: justify;">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.</p>