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March 3, 2026
MUL-UNet: A lightweight multi-weather image restoration network with enhanced edge preservation
RL
Rujia Li
SZ
Shuai Zhang
Shanghai University
GL
Guangxing Liu
National Academy of Governance
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Key Points
Improved edge preservation enhances visual quality of images, especially under adverse weather conditions.
The proposed model significantly reduces artifacts while restoring images, leading to clearer outputs.
Observational assessment using deep learning techniques reveals efficacy across different weather scenarios.
Further validation across diverse environments is needed to confirm generalizability and performance.
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MUL-UNet: A lightweight multi-weather image restoration network with enhanced edge preservation | Synapse
Cite This Study
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Li et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76081c6e9836116a2d4fc
https://doi.org/https://doi.org/10.1016/j.asoc.2026.114756