ViCoW:用于对越南战争图像进行着色和修复的数据集
Duc-Minh Nguyen1, Tri-Nhan Nguyen1, Trung-Quan Hoang1
1FPT University, Viet Nam.
Data in brief
|July 17, 2025
概括
这个数据集提供了1896张来自越南战争电影的图像对,以推进人工智能驱动的历史图像色化和修复研究. 它有助于保护数字遗产,并开发自动化视频修复技术.
科学领域:
- 计算机视觉 计算机视觉
- 数字遗产保护数字遗产的保护
- 人工智能的人工智能
背景情况:
- 越南战争时期的历史电影经常遭受退化,影响了它们的可访问性和研究价值.
- 现有的历史图像修复和彩色化方法需要强大的数据集来进行有效的模型培训和评估.
研究的目的:
- 引入一套新的高分辨率图像对数据集,用于人工智能驱动的历史图像彩色化和恢复.
- 为评估深度学习模型在历史视频处理中的性能提供一个基准.
主要方法:
- 从四部越南电影中系统地提取了1896年的图像对 (原色和灰度).
- 使用ITU-R BT.601亮度公式进行灰度转换.
- 手动选择视觉多样性和上下文相关性,组织成培训,验证和测试集.
主要成果:
- 一个全面的数据集,可以培训和评估用于历史图像修复的AI模型.
- 促进对老化电影质量,时间退化和复杂视觉内容等挑战的研究.
结论:
- 该数据集通过提高历史视觉图像的可访问性,为数字遗产的保护做出了重大贡献.
- 它支持自动化彩色化系统的开发和基于人工智能的静态图像视频恢复.
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