| Issue |
MATEC Web Conf.
Volume 395, 2024
2023 2nd International Conference on Physics, Computing and Mathematical (ICPCM2023)
|
|
|---|---|---|
| Article Number | 01053 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/matecconf/202439501053 | |
| Published online | 15 May 2024 | |
Intelligent enhancement of ancient Chinese murals based on multi-scale parallel structure
Shanghai Foreign Language School Affiliated to SISU, Shanghai, China
* Corresponding author: geyuxin0806@126.com
Ancient mural artwork preserves the historical background and cultural customs of that time through intricate details and bright colors. However, after the natural environment and man-made damage, these works of art are damaged in color, texture and content and lose their quality. In order to identify and enhance murals with large areas of color damage, we propose a multi-scale parallel GAN and parallel Unet structure, which can extract features from multiple scales or images to adapt to the changing scale of the target and provide a more diverse set of features. This structure can reduce the risk of overfitting the training data by learning more general features. The verification results of indicators such as PSNR on the ancient mural data set show that the method has a certain performance improvement effect.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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