Pansharpening aims to sharpen a lowspatial-resolution (LR) multispectral (MS) image using a high-spatial-resolution (HR) panchromatic (Pan) image to obtain the HR MS image. It has been a fundamental and active research topic in remote sensing, and pansharpening methods have been developed for nearly 40 years. While the performance evaluation of pansharpening methods is still based on a small number of individual images, datadriven pansharpening approaches are attracting increasing attention. However, few publicly available benchmark data sets for pansharpening are available, especially large-scale ones. This has been a serious limitation for the future development of pansharpening methods.

中文翻译：

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用于评估全色锐化性能的大规模基准数据集：概述和实施


全色锐化旨在使用高空间分辨率（HR）全色（Pan）图像锐化低空间分辨率（LR）多光谱（MS）图像以获得HR MS图像。它一直是遥感领域的一个基础且活跃的研究课题，全色锐化方法已经发展了近 40 年。虽然全色锐化方法的性能评估仍然基于少量的单个图像，但数据驱动的全色锐化方法正在吸引越来越多的关注。然而，很少有公开可用的全色锐化基准数据集，尤其是大规模数据集。这严重限制了全色锐化方法的未来发展。