光学精密工程2025，Vol.33Issue(8)：1238-1258,21.DOI:10.37188/OPE.20253308.1238
面向单幅遥感图像超分辨率的空间自适应及频率融合网络
Spatial adaptation and frequency fusion network for single remote sensing image super-resolution
摘要
Abstract
Most of the existing methods of remote sensing image super-resolution are unable to fully ex-plore the self-similarity information at hybrid scales and the correlation between cross-scale regions.More-over,these methods ignore the ability of the frequency domain to perceive the high-frequency information of the images.To address this problem,a Spatial Adaptation and Frequency Fusion Network(SAF2Net)was proposed.Firstly,SAF2Net introduced a hybrid-scale spatially-adaptive feature modulation,which adopted a feature pyramid-like approach to obtain discriminative features at different scales and enriched the expression ability of multi-scale features.Subsequently,a global multi-scale field selection block was designed to extract the correlation features of cross-scale regions.On this basis,a spatial adaptively selec-tion block and a frequency separation selection block were introduced to fuse space-frequency complemen-tary information to enhance local features,improving the model's ability to model the high-frequency con-tent of images.Multiple sets of experiments are conducted on two remote sensing image datasets,which indicates that the quantitative evaluation metrics obtained by SAF2Net outperform those of other compara-tive methods.Taking the UCMerced dataset with 3 times super-resolution as an example,the proposed method improves PSNR and SSIM by 0.11 dB and 0.003 3,respectively,in compared with the next best method HAUNet.In terms of the subjective visual quality,SAF2Net is able to recover more clear texture details.The experimental results demonstrate that the SAF2Net proposed is capable of mining the hybrid-scale global information from two different perspectives as well as fusing the space-frequency complementa-ry features effectively,which exhibits competitive performance in the remote sensing image super-resolu-tion task.关键词
遥感图像/超分辨率/混合尺度特征/空频互补信息Key words
remote sensing image/super resolution/hybrid-scale features/space-frequency complemen-tary information分类
信息技术与安全科学引用本文复制引用
杨沂川,马中祺,周新尧,郑福建,黄鸿..面向单幅遥感图像超分辨率的空间自适应及频率融合网络[J].光学精密工程,2025,33(8):1238-1258,21.基金项目
北京市航空智能遥感装备工程技术研究中心开放基金(No.AIRSE202412) （No.AIRSE202412）
国家自然科学基金(No.42071302) （No.42071302）
