MEEAFusion:基于红外和可见图像融合的多尺度边缘增强和联合注意力机制
Yingjiang Xie1, Zhennan Fei1, Da Deng1
1Systems Engineering Institute, Academy of Military Sciences, PLA, Beijing 100166, China.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
这项研究引入了一种新的红外和可见图像融合方法 (MEEAFusion),可以增强特征提取和相互作用. 这种新的方法有效地整合了两种图像类型的细节,以获得卓越的融合性能.
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:
- 红外和可见图像的融合将可见图像的详细特征与红外图像的突出目标相结合.
- 现有的融合方法往往无法完全提取特征或捕捉交叉模式相互作用,限制了融合图像质量.
研究的目的:
- 开发一种新的红外和可见图像融合方法,解决特征提取和交叉模式交互方面的局限性.
- 为了增强精细粒度特征和关键的补充信息在融合图像中的表现.
主要方法:
- 提出了一个多层次的边缘增强和联合关注机制 (MEEAFusion).
- 多尺度卷积核和多尺度梯度余块 (MGRB) 用于特征提取.
- 一个交叉转移注意力融合块 (CAFB) 与联合空间和通道注意力被用于特征交互和改进.
主要成果:
- MEEAFusion方法有效地捕获了高级语义和低级边缘纹理信息.
- 共同注意力机制完善了互补的特征,导致富有共同和补充信息的融合图像.
- 实验表明,纹理细节,红外线目标可见性和边缘轮定义的显著改善.
结论:
- 拟议的MEEAFusion方法在红外和可见图像融合中实现了卓越的性能.
- 该方法增强了多尺度特征和跨模式信息的整合.
- MEEAFusion为高级应用提供了一个强大的解决方案,用于生成高质量的融合图像.
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