Dual-Branch Multi-Level Feature Aggregation Network for Pansharpening
Dear Editor, In pansharpening task, the most existing deep-learning-based pan-sharpening methods fail to fully utilize the different level features, inevitably leading to spectral or spatial distortions. To address this challenge, in this letter, we propose a dual-branch multi-level feature aggregat...
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Veröffentlicht in: | IEEE/CAA journal of automatica sinica 2022-11, Vol.9 (11), p.2023-2026 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Dear Editor, In pansharpening task, the most existing deep-learning-based pan-sharpening methods fail to fully utilize the different level features, inevitably leading to spectral or spatial distortions. To address this challenge, in this letter, we propose a dual-branch multi-level feature aggregation network for pansharpening (DMFANet). The experimental results on the WorldView-II (WV-II) and QuickBird (QB) dataset confirmed the notable superiority of our method over the current state-of-the-art methods from quantitative and qualitative point of view. The source code is available at https://github.com/Gui-Cheng/DMFANet. |
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ISSN: | 2329-9266 2329-9274 |
DOI: | 10.1109/JAS.2022.105956 |