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基于空间增强自注意力网络的无监督全色锐化方法

熊璋玺 李伟 杨飞 林弘杨

中国空间科学技术(中英文)2025,Vol.45Issue(4):48-60,13.
中国空间科学技术(中英文)2025,Vol.45Issue(4):48-60,13.DOI:10.16708/j.cnki.1000-758X.2025.0057

基于空间增强自注意力网络的无监督全色锐化方法

A spatial enhanced Transformer based unsupervised pansharpening method

熊璋玺 1李伟 2杨飞 3林弘杨3

作者信息

  • 1. 北京理工大学 信息科学与电子工程学院,北京 100081
  • 2. 北京理工大学 信息科学与电子工程学院,北京 100081||天基智能信息处理全国重点实验室,北京 100081
  • 3. 长春长光辰谱科技有限公司,长春 130000
  • 折叠

摘要

Abstract

Addressing issues such as insufficient spatial texture and spectral distortion in the fusion of panchromatic and multispectral images,an unsupervised pansharpening method based on spatially enhanced Transformer(Pan-SET)is proposed.Firstly,a multi-scale feature extraction module is designed to obtain features of panchromatic and multi-spectral images at different scales,thereby enhancing the generalization ability of features and the robustness of the model.Secondly,a high-frequency information extraction module is designed to extract high-frequency information from the panchromatic image.The multi-scale features of the panchromatic and multispectral images,after undergoing simple fusion,are jointly input into the designed spatial enhanced Transformer along with the high-frequency information of the panchromatic image.The designed spatial enhanced Transformer consists of a self-attention mechanism and a spatial detail enhancement attention mechanism.The self-attention mechanism can capture self-similarity and extract long-range features,while the spatial detail enhancement attention mechanism ensures that only textures,edges,and detailed parts are enhanced.Finally,after fusion and enhancement through multiple layers of spatial enhancement Transformer,the features are reconstructed into multi-spectral images with high spatial resolution.Comparative experiments are conducted on the GF-2 and WV-3 data in PanCollection dataset,and seven quality evaluation indices are used to objectively assess the quality of the fused images obtained by various methods.The proposed method exhibits the best performance in terms of the quality evaluation index QNR on both datasets,with values of 0.9692 and 0.9327,respectively.The visual effects and quality evaluation indices of the fused images indicate that the proposed method outperforms the comparison methods both subjectively in visual perception and objectively in evaluation,effectively reducing the spatial-spectral distortion of the fused images.

关键词

全色锐化/全色图像/多光谱图像/多尺度特征提取/自注意力网络

Key words

pansharpening/panchromatic/multi-spectral/multi-scale feature extraction/Transformer

分类

信息技术与安全科学

引用本文复制引用

熊璋玺,李伟,杨飞,林弘杨..基于空间增强自注意力网络的无监督全色锐化方法[J].中国空间科学技术(中英文),2025,45(4):48-60,13.

基金项目

国家重点研发计划项目(2021YFB3900502) (2021YFB3900502)

中国空间科学技术(中英文)

OA北大核心

1000-758X

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