通过多个变化约束来消除单一图像雾,以增强视觉传感器
Yuxue Feng1,2, Weijia Zhao1, Luyao Wang1
1College of Sericulture, Textile and Biomass Sciences, Southwest University, Chongqing 400715, China.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
这项研究引入了一种新的雾移除算法,使用多个变化约束来恢复模糊图像中的清晰度和颜色. 该方法有效地提高了可见性,并改善了各种视觉任务的性能.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 遥感 遥感 遥感 遥感
背景情况:
- 视觉传感器捕获的户外图像经常表现出雾引起的退化,损害细节,颜色保真和整体可见性.
- 这种退化严重阻碍了基本的传感和感知系统的性能.
研究的目的:
- 开发一个有效的雾移除算法来增强退化户外图像.
- 通过恢复图像清晰度和色彩活力来提高计算机视觉系统的性能.
主要方法:
- 基于大气散射模型的混合变异框架被开发出来,它包含了传输地图和场景辐射的多个规范化术语.
- 该算法使用lp和l2规范进行传输地图平滑和结构保存,以及加权的l1规范用于场景辐射中的噪声抑制.
- 用重新加权的最小平方策略来解决混合变量模型,然后进行马校正以调整亮度.
主要成果:
- 拟议的算法成功地消除了雾,产生了视觉上令人满意的结果,提高了清晰度和充满活力的颜色.
- 在各种降解场景中展示了卓越的概括能力,包括低光和遥感图像.
- 显著提高了高级视觉任务的性能,例如对象检测和场景理解.
结论:
- 开发的雾移除算法有效地恢复退化的户外图像,提供更好的视觉质量和稳定性.
- 该方法对在具有挑战性的环境条件下提高视觉系统的可靠性和性能充满希望.
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