| 孔令兵,陈昕,连思铭,宋美琦,闻映红,刘少鹏.基于扩散重建与小波频域感知的机载光电图像融合[J].电子测量与仪器学报,2026,40(4):307-316 |
| 基于扩散重建与小波频域感知的机载光电图像融合 |
| Airborne electro-optical image fusion based on diffusion reconstruction andwavelet frequency-domain perception |
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| DOI： |
| 中文关键词: 红外可见光融合 小波频域感知 扩散重建 |
| 英文关键词:infrared-visible image fusion wavelet frequency-domain perception diffusion reconstruction |
| 基金项目:国家自然科学基金“联合基金项目”（U2568201）资助 |
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| Author | Institution |
| Kong Lingbing | School of Automation and Intelligence, Beijing Jiaotong University, Beijing 100044, China |
| Chen Xin | Beijing Institute of Aerospace Control Device, Beijing 100039, China |
| Lian Siming | Beijing Institute of Aerospace Control Device, Beijing 100039, China |
| Song Meiqi | Beijing Institute of Aerospace Control Device, Beijing 100039, China |
| Wen Yinghong | School of Automation and Intelligence, Beijing Jiaotong University, Beijing 100044, China |
| Liu Shaopeng | Beijing Institute of Aerospace Control Device, Beijing 100039, China |
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| 摘要点击次数: 263 |
| 全文下载次数: 133 |
| 中文摘要: |
| 远距离侦察任务中多模态图像融合功能旨在生成兼具各模态显著特征且真实有效的融合图像。为解决远距离目标特征表达真假混杂、纹理结构失真的难题，提出一种扩散重建与小波频域感知融合架构BalanceFusion，旨在提升远距离下红外与可见光图像融合的细节信息表征能力及真实性。该方法首先采用高效图像复原网络增强目标的特征表示能力；然后引入小波条件驱动融合模块，融合频域感知强调目标热辐射轮廓特性，降低因超分辨率过度聚焦于目标而忽略背景结构的影响；最后，逐层聚合模态差异显著的多尺度高频特征信息，确保多模态融合图像包含充分有效的细节信息，在增强特有特征的基础上保持共有特征的真实性。实验结果表明，算法在实飞数据上显著优于现有框架，结构保留与感知质量(Qabf)指标和空间频率(SF)指标分别提升33%和21%，展现了远距离多模态图像融合能力。 |
| 英文摘要: |
| In long-range reconnaissance missions, multimodal image fusion aims to generate fused images that preserve salient features from each modality while maintaining photorealism. To address the challenges of ambiguous feature representation and structural-textural distortion in distant targets, this paper proposes BalanceFusion, a novel fusion architecture integrating diffusion-based reconstruction with wavelet-domain frequency-aware perception, specifically designed to enhance detail representation and fidelity in infrared and visible image fusion under long-range conditions. The proposed method first employs an efficient image restoration network to strengthen target feature representation. Subsequently, a wavelet-conditioned fusion module is introduced to incorporate frequency-domain awareness, emphasizing thermal radiation contours of targets while mitigating the adverse effects of super-resolution methods that overly prioritize foreground targets at the expense of background structural integrity. Finally, modality-specific high-frequency features exhibiting significant differences are hierarchically aggregated across multiple scales to ensure the fused image retains both sufficient discriminative details and authentic shared structures. Experimental results on real-flight datasets demonstrate that the proposed algorithm outperforms state-of-the-art methods, achieving a 33% improvement in the structure-preserving perceptual quality metric Qabf and 21% gain in spatial frequency (SF). |
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