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纹理保护和信息损失最小化方法用于红外和可见图像融合

Qiyuan He^1,2, Yongdong Huang³

¹Institute of Image Understanding Research, North Minzu University, Yinchuan, 750021, China.

Scientific reports

|July 23, 2025

概括

通过保留纹理和最大限度地减少信息丢失,TPFusion增强了红外和可见图像的融合. 这种新的方法在聚变质量和下游任务 (如物体检测) 中实现了卓越的性能.

科学领域:

计算机视觉计算机视觉
图像处理图像处理
人工智能的人工智能

背景情况:

红外和可见图像的融合旨在将不同模式的互补信息结合起来.
现有的融合方法往往无法平衡纹理保护,信息保留和对比度增强.
纹理退化和信息丢失是当前图像融合技术中常见的问题.

研究的目的:

提出TPFusion,一种用于红外和可见图像融合的新方法.
通过保持细粒度纹理和尽量减少信息丢失来解决现有方法的局限性.
为了增强对比度并保持合图像中的清晰边缘.

主要方法:

对于全面的特征捕获,TPFusion采用一个多尺度特征提取模块.
它包含纹理和对比度增强模块,以保存细节和突出特征.
双重注意力融合模块集成了功能,由基于信息内容的丢失函数指导,以尽量减少差异和信息丢失.

主要成果:

在TNO,MSRS和M3FD数据集中,TPFusion展示了优越的融合性能,超过了现有方法.
在诸如平均梯度 (AG),混合/化的质量 (Q_AB/F),相关系数 (CC),空间相关度 (SCD) 和能量 (EN) 等指标中观察到显著改善.
在下游任务中,TPFusion在对象检测中获得了最高的平均精度,在语义细分中获得了第二高的精度.

结论:

TPFusion有效地保留了纹理,并最大限度地减少了红外和可见图像融合中的信息损失.
拟议的方法在图像融合质量和下游应用方面取得了最先进的结果.
TPFusion提供了一个强大的解决方案,可以提高融合红外和可见图像的解释性和实用性.

关键词:

信息理论是信息理论.红外和可见图像融合的红外和可见图像融合.质地保护质地保护

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