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Small Target Extraction Based on Independent Component Analysis for Hyperspectral Imagery

机译:基于独立分量分析的高光谱图像小目标提取

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摘要

A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target information hided in high-dimensional data and projects them into low-dimensional space. Secondly, the feature images are selected with kurtosis . At last, small targets are extracted with histogram image segmentation which has been labeled by skewness.
机译:提出了一种基于独立分量分析的高光谱数据小目标检测方法。在该算法中,首先使用快速独立成分分析(FICA)收集隐藏在高维数据中的目标信息,并将其投影到低维空间中。其次,选择具有峰度的特征图像。最后,用直方图图像分割提取小目标,该直方图图像分割已用偏斜度标记。

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