DLFE-Net:保存细节和删除噪音使用HVI颜色空间用于低光图像增强
Zhaokun He1, Xin Yuan1,2,3, Guozhu Hao3,4
1School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
这项研究引入了一个新的低光图像增强 (LLIE) 网络,该网络可以解决过度曝光和噪音问题. 消光器和低频增强器网络 (DLFE-Net) 有效地保存细节,并消除噪声,以获得卓越的图像质量.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 人工智能的人工智能
背景情况:
- 低光图像增强 (LLIE) 在各种应用中至关重要.
- 现有的方法在过度曝光,细节损失和低光条件下的噪音方面扎.
研究的目的:
- 提出一个新的网络,DLFE-Net,用于有效的低光图像增强.
- 解决LLIE中局部过度曝光,细节保存和噪声消除的挑战.
主要方法:
- 拟议的Denoiser和低频增强器网络 (DLFE-Net) 将RGB转换为HVI颜色空间.
- 它使用低频照明增强器 (LFIE) 模块来保护细节和减轻过度曝光.
- 采用多级门式消噪器 (MSGD) 模块来有效消除噪音.
主要成果:
- 在基准和未配对数据集上,DLFE-Net表现出了比最先进的方法更高的性能.
- 定性和定量分析证实了拟议方法的有效性.
- 废弃性研究验证了DLFE-Net中的单个模块的贡献.
结论:
- DLFE-Net提供了一个强大的解决方案,用于低光图像增强.
- 该网络成功地减轻了过度曝光,保存了细节,并消除了噪音.
- 拟议的LFIE和MSGD模块在解决LLIE关键挑战方面是有效的.
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