دورية أكاديمية
Crossed Dual-Branch U-Net for Hyperspectral Image Super-Resolution
العنوان: | Crossed Dual-Branch U-Net for Hyperspectral Image Super-Resolution |
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المؤلفون: | Jingyi Zhang, Jianjun Liu, Jinlong Yang, Zebin Wu |
المصدر: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2296-2307 (2024) |
بيانات النشر: | IEEE, 2024. |
سنة النشر: | 2024 |
المجموعة: | LCC:Ocean engineering LCC:Geophysics. Cosmic physics |
مصطلحات موضوعية: | Hyperspectral image (HSI), multispectral image, super-resolution transformer, U-Net, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809 |
الوصف: | Hyperspectral images have gained great achievements in many fields, but their low spatial resolution limits the effectiveness in applications. Hyperspectral image super-resolution has emerged as a popular research trend, where high-resolution hyperspectral images are obtained via combining low-resolution hyperspectral images with high-resolution multispectral images. In this process of multimodality data fusion, it is crucial to ensure effective cross-modality information interaction. To generate higher quality fusion results, a crossed dual-branch U-Net is proposed in this article. In specific, we adopt U-Net architecture and introduce a spectral–spatial feature interaction module to capture cross-modality interaction information between two input images. To narrow the gap between downsampling and upsampling processes, a spectral–spatial parallel Transformer is designed as skip connection. This novel design simultaneously learns the long-range dependencies both on spatial and spectral information and provides detailed information for final fusion. In the fusion stage, we adopt a progressive upsampling strategy to refine the generated images. Extensive experiments on several public datasets are conducted to prove the performance of the proposed network. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 2151-1535 |
Relation: | https://ieeexplore.ieee.org/document/10368282/; https://doaj.org/toc/2151-1535 |
DOI: | 10.1109/JSTARS.2023.3345411 |
URL الوصول: | https://doaj.org/article/223218f82b06443aa9187a130750e14d |
رقم الأكسشن: | edsdoj.223218f82b06443aa9187a130750e14d |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 21511535 |
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DOI: | 10.1109/JSTARS.2023.3345411 |