高光谱成像
多光谱图像
计算机科学
图像分辨率
人工智能
图像融合
计算机视觉
融合
遥感
图像(数学)
网(多面体)
全光谱成像
棱锥(几何)
空间分析
模式识别(心理学)
数学
地理
哲学
语言学
几何学
作者
Shuaiqi Liu,Siyuan Liu,Shichong Zhang,Bing Li,Weiming Hu,Yudong Zhang
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:60: 1-16
被引量:12
标识
DOI:10.1109/tgrs.2022.3217168
摘要
Compared with traditional remoting image, there is a large amount of spectral information in the hyperspectral image (HSI), which makes HSI better reflect the actual condition of surface features.However, due to the limitations of imaging conditions, HSI tends to have a lower spatial resolution.In order to overcome this issue, we propose a spectral-spatial attention-based U-Net named SSAU-Net for HSI and multispectral image (MSI) fusion.The SSAU-Net constructs a spectral-spatial attention module by a coordinate-attention (CA) module and an efficient pyramid split attention (ESPA) module, which can enhance the image's spectral information and spatial information.Meanwhile, the proposed network fully extracts the shallow and deep features of the images, and finally generates high-resolution (HR) hyperspectral images.Compared with state-of-the-art HSI-MSI fusion methods, the experimental results verify that the proposed method has a better subjective and objective fusion effect.
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