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\nThe increasing demand for high spatial resolution in remote sensing imagery has led to the necessity of super-resolution (SR) algorithms that convert low-resolution (LR) images into high-resolution (HR) ones. To address this need, we introduce SEN2NAIP, a large remote sensing dataset designed to support conventional and reference-based SR model. This dataset is a variation of the SEN2NAIP `synthetic large dataset`. We select Sentinel-2 images that fall within a 30-day window of the corresponding NAIP image. Histogram matching is used to ensure consistent color distribution between the LR and HR images. A manual visual inspection is then conducted to discard any poor-quality images. The LR image is generated following the SEN2NAIPmethodology.\n
\n\n*The spatial coverage of the dataset. The patch size is LR 130 \u00d7 130 and HR 520 \u00d7 520, respectively.",
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"title": "A larget dataset for super-resolution of Sentinel-2",
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