WIFE-Fusion:Wavelet-aware Intra-inter Frequency Enhancement for Multi-model Image Fusion

• URL: http://arxiv.org/abs/2506.03555v1
• Date: Wed, 04 Jun 2025 04:18:32 GMT
• Title: WIFE-Fusion:Wavelet-aware Intra-inter Frequency Enhancement for Multi-model Image Fusion
• Authors: Tianpei Zhang, Jufeng Zhao, Yiming Zhu, Guangmang Cui,
• Abstract summary: Multimodal image fusion effectively aggregates information from diverse modalities.<n>Existing methods often neglect frequency-domain feature exploration and interactive relationships.<n>We propose wavelet-aware Intra-inter Frequency Enhancement Fusion (WIFE-Fusion), a multimodal image fusion framework based on frequency-domain components interactions.
• Score: 8.098063209250684
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multimodal image fusion effectively aggregates information from diverse modalities, with fused images playing a crucial role in vision systems. However, existing methods often neglect frequency-domain feature exploration and interactive relationships. In this paper, we propose wavelet-aware Intra-inter Frequency Enhancement Fusion (WIFE-Fusion), a multimodal image fusion framework based on frequency-domain components interactions. Its core innovations include: Intra-Frequency Self-Attention (IFSA) that leverages inherent cross-modal correlations and complementarity through interactive self-attention mechanisms to extract enriched frequency-domain features, and Inter-Frequency Interaction (IFI) that enhances enriched features and filters latent features via combinatorial interactions between heterogeneous frequency-domain components across modalities. These processes achieve precise source feature extraction and unified modeling of feature extraction-aggregation. Extensive experiments on five datasets across three multimodal fusion tasks demonstrate WIFE-Fusion's superiority over current specialized and unified fusion methods. Our code is available at https://github.com/Lmmh058/WIFE-Fusion.

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