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An evaluation of three endmember extraction algorithms: ATGP, ICA-EEA VCA

机译:对三种端成员提取算法的评估:ATGP,ICA-EEA和VCA

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In this paper, we evaluate three endmember extraction algorithms for use in hyperspectral imagery unmixing: automatic target generation procedure (ATGP), independent component analysis endmember extraction algorithm (ICA-EEA), and vertex component analysis (VCA). We evaluate each algorithm's ability to find known pure pixels in a scene of simulated data. Several variations of simulated data are used to thoroughly examine the unmixing limits of each algorithm.
机译:在本文中,我们评估了用于高光谱图像分解的三种末端成员提取算法:自动目标生成过程(ATGP),独立成分分析末端成员提取算法(ICA-EEA)和顶点成分分析(VCA)。我们评估每种算法在模拟数据场景中找到已知纯像素的能力。模拟数据的几种变体用于彻底检查每种算法的混合极限。

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