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Ameliorating the spatial resolution of Hyperion hyperspectral data

机译:改善Hyperion高光谱数据的空间分辨率

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In this study seven fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are onboard on EO-1 satellite and the data are collected simultaneously. The panchromatic data has a spatial resolution of 10m while the hyperspectral data has a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data. The area of study is the broader area of North Western Athens near to Thrakomakedones village.
机译:在这项研究中,七种融合技术,尤其是Ehlers,Gram-Schmidt,高通​​滤波器,局部均值匹配(LMM),局部均值和方差匹配(LMVM),Pansharp和PCA被用于Hyperion高光谱数据与ALI全色数据。两个传感器都安装在EO-1卫星上,并且同时收集数据。全色数据的空间分辨率为10m,而高光谱数据的空间分辨率为30m。所有融合技术均设计用于经典的多光谱数据。因此,用高光谱数据研究常用融合算法的评估是非常有趣的。研究领域是雅典西北部靠近Thrakomakedones村的大片地区。

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