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SASM-DOS:为烟雾环境构建大气散射模型和用于烟雾图像澄清的算法

Xingang Wang, Yalin Yu, Junwei Tian

|December 19, 2025

概括

这项研究引入了用于烟雾环境的新型图像澄清算法,提高了在消防救援和工业监控等具有挑战性的条件下的可见性. 该方法有效地减少噪音,并纠正照明问题,以获得更清晰的图像.

科学领域:

计算机视觉计算机视觉
图像处理图像处理
环境传感器环境传感器

背景情况:

烟雾环境带来了显著的图像退化挑战,包括复杂的噪音和不均的照明.
现有的图像处理方法与各种烟雾介质的独特散射特性作斗争.

研究的目的:

开发一种有效的图像澄清算法,专门用于充满烟雾的环境.
提高视觉质量,并为关键应用提供强大的技术支持.

主要方法:

一个多个阶段的框架,包含多个尺度的分层排序和超像素细分 (SLIC) 用于大气光估计.
一种联合传导率估计方法和LMS颜色空间转换,以提高颜色保真度和对比度.
利用交叉双边过来完善大气光估计和通道线性拉伸以扩大动态范围.

主要成果:

拟议的算法显著改善了烟雾图像中的细节纹理和颜色保真度.
与现有方法相比,在所有定量评估指标上表现出卓越的表现.
主观的视觉评估证实了处理图像的提高清晰度和细节.

结论:

开发的烟雾环境图像澄清算法为具有挑战性的视觉条件提供了强大的解决方案.
该方法为消防救援,工业监控和自动驾驶等应用提供了宝贵的技术支持.

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