Methods › Computer Vision › Convolutional Neural Networks › PanNet
Pansharpening Network
PanNet
Introduced by Junfeng Yang et al. in PanNet: A Deep Network Architecture for Pan-Sharpening
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
We propose a deep network architecture for the pansharpening problem called PanNet. We incorporate domain-specific knowledge to design our PanNet architecture by focusing on the two aims of the pan-sharpening problem: spectral and spatial preservation. For spectral preservation, we add up-sampled multispectral images to the network output, which directly propagates the spectral information to the reconstructed image. To preserve the spatial structure, we train our network parameters in the high-pass filtering domain rather than the image domain. We show that the trained network generalizes well to images from different satellites without needing retraining. Experiments show significant improvement over state-of-the-art methods visually and in terms of standard quality metrics.
Papers archive 2025-07-28
4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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SDRCNN: A single-scale dense residual connected convolutional neural network for pansharpening 1 Jul 2023 · 0 repositories · arXiv:2307.00327
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Proximal PanNet: A Model-Based Deep Network for Pansharpening 12 Feb 2022 · 0 repositories · arXiv:2203.04286
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Pansharpening by convolutional neural networks in the full resolution framework 16 Nov 2021 · 2 repositories · arXiv:2111.08334
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PanNet: A Deep Network Architecture for Pan-Sharpening 1 Oct 2017 · 0 repositories
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Pansharpening | 3 |
| Deep Learning | 1 |
| Image Super-Resolution | 1 |
| Super-Resolution | 1 |
| satellite image super-resolution | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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