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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 1, 2024.
Abstract: With the promotion and development of Chinese painting and the advancement of photography technology, people can appreciate various types of Chinese paintings through image and other methods. However, Chinese painting images in low-light environments face the problem of extreme uneven brightness distribution. The currently proposed solutions for this problem are not sufficient. Therefore, this research proposes a brightness equalization algorithm for Chinese painting pigments in low-light environments based on region division. This algorithm also utilizes guided filtering for image denoising. In performance testing, the proposed method has a runtime of 16.63 seconds under a scaling factor of 1 and a runtime of 8.37 seconds under a scaling factor of 0.1, which are the fastest among the compared algorithms. In simulation experiments, the brightness equalization value of the proposed method is 198.93, which is listed at the best among all the compared algorithms. This research provides a valuable research direction for the brightness equalization of Chinese painting pigments.
Lijuan Cheng, “Brightness Equalization Algorithm for Chinese Painting Pigments in Low-Light Environment Based on Region Division” International Journal of Advanced Computer Science and Applications(IJACSA), 15(1), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150111
@article{Cheng2024,
title = {Brightness Equalization Algorithm for Chinese Painting Pigments in Low-Light Environment Based on Region Division},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150111},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150111},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {1},
author = {Lijuan Cheng}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.