标题： HyFusion：高光谱图像融合的增强接收域变换器 显示英文标题

标题： HyFusion: Enhanced Reception Field Transformer for Hyperspectral Image Fusion

摘要： 高光谱图像（HSI）融合解决了从高分辨率多光谱图像（HR-MSIs）和低分辨率HSI（LR-HSIs）重建高分辨率HSI（HR-HSIs）的挑战，鉴于获取高质量HSI的高成本和硬件限制，这是一个关键任务。虽然现有方法利用了空间和光谱关系，但它们通常受到有限的感受野和特征利用不足的限制，导致性能不佳。此外，高质量HSI数据的稀缺性突显了高效数据利用的重要性，以最大化重建质量。为了解决这些问题，我们提出了HyFusion，一种新颖的双耦合网络（DCN）框架，旨在增强跨域特征提取并实现有效的特征图重用。该框架首先通过专用子网络处理HR-MSI和LR-HSI输入，在特征提取过程中相互增强，保留互补的空间和光谱细节。其核心是增强感受野块（ERFB），它结合了移动窗口注意力和密集连接以扩展感受野，有效捕捉长距离依赖关系，同时最小化信息丢失。大量实验表明，HyFusion在HR-MSI/LR-HSI融合中实现了最先进的性能，在保持紧凑模型大小和计算效率的同时显著提高了重建质量。通过将增强的感受野和特征图重用集成到耦合网络架构中，HyFusion为资源受限场景下的HSI融合提供了一个实用且有效的解决方案，在高光谱成像领域设定了新的基准。我们的代码将公开可用。 显示英文摘要

摘要： Hyperspectral image (HSI) fusion addresses the challenge of reconstructing High-Resolution HSIs (HR-HSIs) from High-Resolution Multispectral images (HR-MSIs) and Low-Resolution HSIs (LR-HSIs), a critical task given the high costs and hardware limitations associated with acquiring high-quality HSIs. While existing methods leverage spatial and spectral relationships, they often suffer from limited receptive fields and insufficient feature utilization, leading to suboptimal performance. Furthermore, the scarcity of high-quality HSI data highlights the importance of efficient data utilization to maximize reconstruction quality. To address these issues, we propose HyFusion, a novel Dual-Coupled Network (DCN) framework designed to enhance cross-domain feature extraction and enable effective feature map reusing. The framework first processes HR-MSI and LR-HSI inputs through specialized subnetworks that mutually enhance each other during feature extraction, preserving complementary spatial and spectral details. At its core, HyFusion utilizes an Enhanced Reception Field Block (ERFB), which combines shifting-window attention and dense connections to expand the receptive field, effectively capturing long-range dependencies while minimizing information loss. Extensive experiments demonstrate that HyFusion achieves state-of-the-art performance in HR-MSI/LR-HSI fusion, significantly improving reconstruction quality while maintaining a compact model size and computational efficiency. By integrating enhanced receptive fields and feature map reusing into a coupled network architecture, HyFusion provides a practical and effective solution for HSI fusion in resource-constrained scenarios, setting a new benchmark in hyperspectral imaging. Our code will be publicly available.