红外和可见图像融合算法基于双域转换过器和对比转换特征提取
Xu Ma1,2, Tianqi Li2, Jun Deng1
1College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Sensors (Basel, Switzerland)
|June 27, 2024
概括
这项研究引入了一种新的可见和红外图像融合算法 (DDCTFuse),以克服色彩扭曲和细节丢失. DDCTFuse方法提高了目标的分辨率和场景信息,改善了整体图像对比度.
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:
- 可见和红外图像融合面临着诸如色彩扭曲,纹理损失和模糊边缘等挑战.
- 现有的融合方法与不完整的细节提取和对比度损失作斗争.
研究的目的:
- 提出一个新的图像融合算法,DDCTFuse,解决当前可见和红外融合技术的局限性.
- 为了提高目标的清晰度,保存纹理细节,并增强融合图像中的对比度.
主要方法:
- 使用自适应高通波器将图像分解为高频和低频组件.
- 新型非线性转换函数用于特征提取以解决对比度损失.
- 空间域逻辑过器用于优化融合结果,包括颜色校正和边缘增强.
主要成果:
- 在基准数据集 (LLVIP,MSRS,INO,Roadscene) 上,DDCTFuse算法与九种经典算法相比,表现优越.
- 融合的图像展示了不同的目标,全面的场景信息,并显著改善了图像对比度.
- 有效地解决了传统融合工艺中固有的颜色损失和边缘模糊问题.
结论:
- 拟议的DDCTFuse算法为可见和红外图像融合提供了一个强大的解决方案.
- 该方法通过保留细节和改善对比度,显著提高了图像质量.
- DDCTFuse为需要高质量的融合图像的应用提供了宝贵的进步.
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