改进了暗通道先验单个图像除雾技术,使用图像分割和联合过
Zhenguo Lu1, Hongbin Wang1, Mingyan Wang2
1College of Transportation, Shandong University of Science and Technology, Qingdao, China.
Science progress
|February 5, 2024
概括
这项研究引入了一种改进的暗通道先导技术,用于清除图像的雾,特别是在天空区域. 该方法有效地划分天空区域,减少光环工件,并增强图像细节恢复以获得更清晰的视觉效果.
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:
- 模糊的图像在分析中存在挑战,原因是低清晰度和模糊的细节.
- 现有的雾清除技术与天空区域进行斗争,导致误估了大气光和光环文物.
研究的目的:
- 提出一个改进的暗通道之前的单图像脱雾技术.
- 为了有效地划分天空区域,并减轻模糊图像中的光环工件.
- 为了提高细节的恢复和视觉质量,脱雾的图像.
主要方法:
- 使用K-平均线聚类和概率密度分布函数进行图像细分,以估计大气照明值.
- 通过联合过 (快速引导过和加权最小平方过) 来优化图像传导率图.
- 以马校正和自动水平优化为亮度和对比度增强的后处理.
主要成果:
- 在模糊的图像中,天空和非天空区域的有效细分.
- 与传统的黑暗通道之前的方法相比,大光文物的显著抑制.
- 改进了图像细节恢复和整体视觉质量在脱雾图像.
结论:
- 拟议的技术在清除天空区域的图像方面提供了卓越的性能.
- 它有效地解决了现有方法的局限性,提供了更好的主观和客观评估.
- 这种方法提高了图像脱雾在具有挑战性的环境中的实际适用性.
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