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Pansharpening of hyperspectral images: Exploiting data acquired by multiple platforms

机译:全光谱高光谱图像:利用多个平台获取的数据

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Accurate representations of the Earth surface in both spatial and spectral domains are highly desirable in many applications using remotely sensed data. An effective solution is achieved by combining hyperspectral data, which are characterized by a high spectral diversity, with high spatial resolution images, collected by multispectral or panchromatic sensors. In this work, we compare the outcomes provided by fusing single-platform or multi-platform data. We demonstrate that the optimal choice depends on the target spatial resolution to be achieved. To this aim, real images collected by the Hyperion sensor are combined with data acquired by the ALI sensor or the QuickBird sensor assessing the fused outcomes at reduced resolution.
机译:在许多使用遥感数据的应用中,非常需要在空间域和光谱域中均能准确表示地球表面。一种有效的解决方案是将高光谱数据(其特征在于高光谱多样性)与由多光谱或全色传感器收集的高空间分辨率图像相结合,从而实现有效的解决方案。在这项工作中,我们比较了融合单平台或多平台数据所提供的结果。我们证明了最佳选择取决于要实现的目标空间分辨率。为此,将Hyperion传感器收集的真实图像与ALI传感器或QuickBird传感器获取的数据结合在一起,以降低的分辨率评估融合结果。

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