噪音感知红外偏振图像融合基于突出先前与注意引导过网络的突出先前与注意引导过网络
Optics express
|September 15, 2023
概括
这项研究引入了一种新的红外偏振图像融合方法. 它有效地抑制噪音,并在复杂的环境中保留目标特征,改善图像可见性和细节.
科学领域:
- 光学和光子学 在光学和光子学.
- 图像处理 图像处理
- 遥感 遥感 遥感 遥感
背景情况:
- 红外极化成像将强度和极化数据融合在一起,以提高可见性.
- 复杂的环境引入噪音,降低极化成像性能.
- 目前使用红外强度 (S0) 和线性极化度 (DoLP) 的融合方法忽略了噪声,降低了效率.
研究的目的:
- 开发一种先进的红外极化图像融合方法,对噪声具有强度.
- 通过结合偏振角度 (AoP) 和偏振距离 (PD) 来增强突出目标特征的提取.
- 通过解决噪声干扰,提高复杂环境中的聚变性能.
主要方法:
- 提出了一种基于极化突出先验的新型聚变方法.
- 极化角度 (AoP) 和极化距离 (PD) 被引入,以扩展DoLP用于突出特征提取.
- 使用交叉注意力的注意引导过网络被构建以基于S0和DoLP特征分布生成融合过器.
主要成果:
- 拟议的方法有效地抑制了红外极化图像中的噪声干扰.
- 突出的目标特征保存良好,从而提高了图像细节和可见性.
- 定量和定性实验表明,与现有的融合技术相比,性能优越.
结论:
- 开发的注意力引导融合方法显著改善了红外极化图像融合.
- 这种方法在具有挑战性的成像条件下提供了一种强大的解决方案,用于抑制噪音和保存突出特征.
- 这种方法提高了红外极化成像在复杂环境中的实际应用.
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