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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 MeanMatching (LMM), Local Mean and Variance Matching (LMVM), Pansharp and PCA, were used for the fusion ofHyperion hyperspectral data with ALI panchromatic data. Both sensors are onboard on EO-1 satellite and the data arecollected simultaneously. The panchromatic data has a spatial resolution of 10m while the hyperspectral data has aspatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quiteinteresting to investigate the assessment of the common used fusion algorithms with the hyperspectral data. The area ofstudy is the broader area of North Western Athens near to Thrakomakedones village.
机译:在这项研究中,七种融合技术和更尤其是Ehlers,Gram-Schmidt,高通​​滤波器,局部意图(LMM),局部均值和方差匹配(LMVM),Pansharp和PCA,用于渗透Hyperspectral数据与Ali Panchromatic数据。两个传感器都在EO-1卫星上是船上的,并且数据同时进行数据。 Panchromatic数据具有10米的空间分辨率,而超光谱数据具有30m的数量分辨率。所有融合技术都设计用于经典多光谱数据。因此,探讨使用高光谱数据的常用融合算法的评估是非常有趣的。 Study的地区是北部雅典的更广泛的Thrakom卵囊村。

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